Hugging Face's logo

Datasets:
kamel-usp
/
jbcs2025_experiments_report

Modalities:
Tabular
Text
Formats:
parquet
Size:
< 1K
Tags:
automatic-essay-scoring
portuguese
text-classification
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
xet
Community
3
igorcs commited on
Commit
7edc9b5
·
1 Parent(s): 206c729

Adicionando o gpt4-grader-C5

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. README.md +109 -109
  2. boostrap_confidence_intervals-00000-of-00001.parquet +2 -2
  3. evaluation_results-00000-of-00001.parquet +2 -2
  4. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C1-essay_only/evaluation_results.csv +2 -2
  5. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C1-full_context/evaluation_results.csv +2 -2
  6. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C2-essay_only/evaluation_results.csv +2 -2
  7. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C2-full_context/evaluation_results.csv +2 -2
  8. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C3-essay_only/evaluation_results.csv +2 -2
  9. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C3-full_context/evaluation_results.csv +2 -2
  10. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C4-essay_only/evaluation_results.csv +2 -2
  11. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C4-full_context/evaluation_results.csv +2 -2
  12. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C5-essay_only/evaluation_results.csv +2 -2
  13. runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C5-full_context/evaluation_results.csv +2 -2
  14. runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/.hydra/config.yaml +35 -0
  15. runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/.hydra/hydra.yaml +155 -0
  16. runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/.hydra/overrides.yaml +1 -0
  17. runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/bootstrap_confidence_intervals.csv +2 -0
  18. runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/evaluation_results.csv +2 -0
  19. runs/{slm_decoder_models/phi-4/jbcs2025_phi-4-phi4_classification_lora-C5-full_context-phi4_classification_lora-C5-full_context/jbcs2025_phi-4-phi4_classification_lora-C5-full_context-phi4_classification_lora-C5-full_context_inference_results.jsonl → api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only_inference_results.jsonl} +0 -0
  20. runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/run_inference_experiment.log +0 -0
  21. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C1-essay_only/evaluation_results.csv +2 -2
  22. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C1-full_context/evaluation_results.csv +2 -2
  23. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C2-essay_only/evaluation_results.csv +2 -2
  24. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C2-full_context/evaluation_results.csv +2 -2
  25. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C3-essay_only/evaluation_results.csv +2 -2
  26. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C3-full_context/evaluation_results.csv +2 -2
  27. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C4-essay_only/evaluation_results.csv +2 -2
  28. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C4-full_context/evaluation_results.csv +2 -2
  29. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C5-essay_only/evaluation_results.csv +2 -2
  30. runs/{slm_decoder_models/phi-3.5/jbcs2025_Phi-3.5-mini-instruct-phi35_classification_lora-C5-full_context-phi35_classification_lora-C5-full_context/jbcs2025_Phi-3.5-mini-instruct-phi35_classification_lora-C5-full_context-phi35_classification_lora-C5-full_context_inference_results.jsonl → api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C5-essay_only/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only_inference_results.jsonl} +0 -0
  31. runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C5-full_context/evaluation_results.csv +2 -2
  32. runs/api_models/sabia-3/sabia-3-zero-shot-C1-essay_only/evaluation_results.csv +2 -2
  33. runs/api_models/sabia-3/sabia-3-zero-shot-C1-full_context/evaluation_results.csv +2 -2
  34. runs/api_models/sabia-3/sabia-3-zero-shot-C2-essay_only/evaluation_results.csv +2 -2
  35. runs/api_models/sabia-3/sabia-3-zero-shot-C2-full_context/evaluation_results.csv +2 -2
  36. runs/api_models/sabia-3/sabia-3-zero-shot-C3-essay_only/evaluation_results.csv +2 -2
  37. runs/api_models/sabia-3/sabia-3-zero-shot-C3-full_context/evaluation_results.csv +2 -2
  38. runs/api_models/sabia-3/sabia-3-zero-shot-C4-essay_only/evaluation_results.csv +2 -2
  39. runs/api_models/sabia-3/sabia-3-zero-shot-C4-full_context/evaluation_results.csv +2 -2
  40. runs/api_models/sabia-3/sabia-3-zero-shot-C5-essay_only/evaluation_results.csv +2 -2
  41. runs/api_models/sabia-3/sabia-3-zero-shot-C5-full_context/evaluation_results.csv +2 -2
  42. runs/base_models/bertimbau/jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only/evaluation_results.csv +2 -2
  43. runs/base_models/bertimbau/jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only/evaluation_results.csv +2 -2
  44. runs/base_models/bertimbau/jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only/evaluation_results.csv +2 -2
  45. runs/base_models/bertimbau/jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only/evaluation_results.csv +2 -2
  46. runs/base_models/bertimbau/jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only/evaluation_results.csv +2 -2
  47. runs/base_models/mbert/jbcs2025_mbert_base-C1-encoder_classification-C1-essay_only/evaluation_results.csv +2 -2
  48. runs/base_models/mbert/jbcs2025_mbert_base-C2-encoder_classification-C2-essay_only/evaluation_results.csv +2 -2
  49. runs/base_models/mbert/jbcs2025_mbert_base-C3-encoder_classification-C3-essay_only/evaluation_results.csv +2 -2
  50. runs/base_models/mbert/jbcs2025_mbert_base-C4-encoder_classification-C4-essay_only/evaluation_results.csv +2 -2
README.md CHANGED
@@ -1,109 +1,109 @@
1
- ---
2
- pretty_name: "JBCS2025: AES Experimental Logs and Predictions"
3
- license: "cc-by-nc-4.0"
4
- configs:
5
- - config_name: evaluation_results
6
- data_files:
7
- - split: evaluation_results
8
- path: evaluation_results-*.parquet
9
- - config_name: bootstrap_confidence_intervals
10
- data_files:
11
- - split: boostrap_confidence_intervals
12
- path: boostrap_confidence_intervals-*.parquet
13
- tags:
14
- - automatic-essay-scoring
15
- - portuguese
16
- - text-classification
17
- ---
18
-
19
- # JBCS 2025: Experimental Artefacts for AES in Brazilian Portuguese
20
-
21
- This repository contains all experimental artefacts (logs, configurations, predictions, and evaluation results) described in the paper:
22
-
23
- > **Exploring the Usage of LLMs for Automatic Essay Scoring in Brazilian Portuguese Essays**
24
- > André Barbosa, Igor Cataneo Silveira, Denis Deratani Mauá
25
- > TODO
26
-
27
- ---
28
-
29
- ## 📦 What's in this dataset repo?
30
-
31
- This dataset is **not a training dataset**. Instead, it provides comprehensive logs and outputs from experiments evaluating different language models for Automatic Essay Scoring (AES) tasks in Brazilian Portuguese.
32
-
33
- Specifically, it contains:
34
-
35
- - 🔁 **JSONL files**: raw predictions from each evaluated model.
36
- - 📊 **CSV files**: detailed performance metrics (Quadratic Weighted Kappa, F1-score, etc.).
37
- - ⚙️ **YAML files**: complete Hydra configurations for reproducibility.
38
- - 📋 **Log files**: logs detailing each evaluation run.
39
-
40
- ---
41
-
42
- ## 📚 Related Collection
43
-
44
- All models and datasets related to this work are available in the Hugging Face collection:
45
-
46
- 🔗 [**AES JBCS2025 Collection**](https://huggingface.co/collections/kamel-usp/jbcs2025-67d5e73a4b89c1f0c878159c)
47
-
48
- ---
49
-
50
- ## 📊 Evaluated Models
51
-
52
- The table below lists all models trained and evaluated for each essay competence (C1 to C5), along with direct links to their Hugging Face repository pages:
53
-
54
- | Model | Architecture | Training Type | Link |
55
- |-------|--------------|---------------|------|
56
- | mbert_base-C1 | Encoder-only | Fine-tuned | [mbert_base-C1](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C1) |
57
- | mbert_base-C2 | Encoder-only | Fine-tuned | [mbert_base-C2](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C2) |
58
- | mbert_base-C3 | Encoder-only | Fine-tuned | [mbert_base-C3](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C3) |
59
- | mbert_base-C4 | Encoder-only | Fine-tuned | [mbert_base-C4](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C4) |
60
- | mbert_base-C5 | Encoder-only | Fine-tuned | [mbert_base-C5](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C5) |
61
- | bertimbau_base-C1 | Encoder-only | Fine-tuned | [bertimbau_base-C1](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C1) |
62
- | bertimbau_base-C2 | Encoder-only | Fine-tuned | [bertimbau_base-C2](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C2) |
63
- | bertimbau_base-C3 | Encoder-only | Fine-tuned | [bertimbau_base-C3](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C3) |
64
- | bertimbau_base-C4 | Encoder-only | Fine-tuned | [bertimbau_base-C4](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C4) |
65
- | bertimbau_base-C5 | Encoder-only | Fine-tuned | [bertimbau_base-C5](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C5) |
66
- | bertimbau_large-C1 | Encoder-only | Fine-tuned | [bertimbau_large-C1](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C1) |
67
- | bertimbau_large-C2 | Encoder-only | Fine-tuned | [bertimbau_large-C2](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C2) |
68
- | bertimbau_large-C3 | Encoder-only | Fine-tuned | [bertimbau_large-C3](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C3) |
69
- | bertimbau_large-C4 | Encoder-only | Fine-tuned | [bertimbau_large-C4](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C4) |
70
- | bertimbau_large-C5 | Encoder-only | Fine-tuned | [bertimbau_large-C5](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C5) |
71
- | llama3-8b-C1 | Decoder-only | LoRA | [llama3-8b-C1](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C1) |
72
- | llama3-8b-C2 | Decoder-only | LoRA | [llama3-8b-C2](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C2) |
73
- | llama3-8b-C3 | Decoder-only | LoRA | [llama3-8b-C3](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C3) |
74
- | llama3-8b-C4 | Decoder-only | LoRA | [llama3-8b-C4](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C4) |
75
- | llama3-8b-C5 | Decoder-only | LoRA | [llama3-8b-C5](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C5) |
76
- | phi3.5-C1 | Decoder-only | LoRA | [phi3.5-C1](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C1) |
77
- | phi3.5-C2 | Decoder-only | LoRA | [phi3.5-C2](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C2) |
78
- | phi3.5-C3 | Decoder-only | LoRA | [phi3.5-C3](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C3) |
79
- | phi3.5-C4 | Decoder-only | LoRA | [phi3.5-C4](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C4) |
80
- | phi3.5-C5 | Decoder-only | LoRA | [phi3.5-C5](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C5) |
81
- | phi4-C1 | Decoder-only | LoRA | [phi4-C1](https://huggingface.co/kamel-usp/jbcs2025_phi4-C1) |
82
- | phi4-C2 | Decoder-only | LoRA | [phi4-C2](https://huggingface.co/kamel-usp/jbcs2025_phi4-C2) |
83
- | phi4-C3 | Decoder-only | LoRA | [phi4-C3](https://huggingface.co/kamel-usp/jbcs2025_phi4-C3) |
84
- | phi4-C4 | Decoder-only | LoRA | [phi4-C4](https://huggingface.co/kamel-usp/jbcs2025_phi4-C4) |
85
- | phi4-C5 | Decoder-only | LoRA | [phi4-C5](https://huggingface.co/kamel-usp/jbcs2025_phi4-C5) |
86
-
87
- 🧠 Additionally, **API-only models** (e.g., DeepSeek-R1, ChatGPT-4o, Sabiá-3) were evaluated but are not hosted on the Hub. Their predictions and logs are still included in this dataset.
88
-
89
- ---
90
-
91
- ## 🧪 How to Use this Dataset
92
-
93
- You can easily load the data using Hugging Face datasets library:
94
-
95
- ```python
96
- from datasets import load_dataset
97
- ds = load_dataset("kamel-usp/jbcs2025_experiments", split="runs")
98
- ```
99
-
100
- ---
101
- ## 📄 License and Citation
102
-
103
- This work is licensed under the [Creative Commons Attribution 4.0 International License (CC-BY-4.0)](https://creativecommons.org/licenses/by/4.0/).
104
-
105
- If you use these artefacts, please cite our paper:
106
-
107
- ```bibtex
108
- TODO
109
- ```
 
1
+ ---
2
+ pretty_name: "JBCS2025: AES Experimental Logs and Predictions"
3
+ license: "cc-by-nc-4.0"
4
+ configs:
5
+ - config_name: evaluation_results
6
+ data_files:
7
+ - split: evaluation_results
8
+ path: evaluation_results-*.parquet
9
+ - config_name: bootstrap_confidence_intervals
10
+ data_files:
11
+ - split: boostrap_confidence_intervals
12
+ path: boostrap_confidence_intervals-*.parquet
13
+ tags:
14
+ - automatic-essay-scoring
15
+ - portuguese
16
+ - text-classification
17
+ ---
18
+
19
+ # JBCS 2025: Experimental Artefacts for AES in Brazilian Portuguese
20
+
21
+ This repository contains all experimental artefacts (logs, configurations, predictions, and evaluation results) described in the paper:
22
+
23
+ > **Exploring the Usage of LLMs for Automatic Essay Scoring in Brazilian Portuguese Essays**
24
+ > André Barbosa, Igor Cataneo Silveira, Denis Deratani Mauá
25
+ > TODO
26
+
27
+ ---
28
+
29
+ ## 📦 What's in this dataset repo?
30
+
31
+ This dataset is **not a training dataset**. Instead, it provides comprehensive logs and outputs from experiments evaluating different language models for Automatic Essay Scoring (AES) tasks in Brazilian Portuguese.
32
+
33
+ Specifically, it contains:
34
+
35
+ - 🔁 **JSONL files**: raw predictions from each evaluated model.
36
+ - 📊 **CSV files**: detailed performance metrics (Quadratic Weighted Kappa, F1-score, etc.).
37
+ - ⚙️ **YAML files**: complete Hydra configurations for reproducibility.
38
+ - 📋 **Log files**: logs detailing each evaluation run.
39
+
40
+ ---
41
+
42
+ ## 📚 Related Collection
43
+
44
+ All models and datasets related to this work are available in the Hugging Face collection:
45
+
46
+ 🔗 [**AES JBCS2025 Collection**](https://huggingface.co/collections/kamel-usp/jbcs2025-67d5e73a4b89c1f0c878159c)
47
+
48
+ ---
49
+
50
+ ## 📊 Evaluated Models
51
+
52
+ The table below lists all models trained and evaluated for each essay competence (C1 to C5), along with direct links to their Hugging Face repository pages:
53
+
54
+ | Model | Architecture | Training Type | Link |
55
+ |-------|--------------|---------------|------|
56
+ | mbert_base-C1 | Encoder-only | Fine-tuned | [mbert_base-C1](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C1) |
57
+ | mbert_base-C2 | Encoder-only | Fine-tuned | [mbert_base-C2](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C2) |
58
+ | mbert_base-C3 | Encoder-only | Fine-tuned | [mbert_base-C3](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C3) |
59
+ | mbert_base-C4 | Encoder-only | Fine-tuned | [mbert_base-C4](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C4) |
60
+ | mbert_base-C5 | Encoder-only | Fine-tuned | [mbert_base-C5](https://huggingface.co/kamel-usp/jbcs2025_mbert_base-C5) |
61
+ | bertimbau_base-C1 | Encoder-only | Fine-tuned | [bertimbau_base-C1](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C1) |
62
+ | bertimbau_base-C2 | Encoder-only | Fine-tuned | [bertimbau_base-C2](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C2) |
63
+ | bertimbau_base-C3 | Encoder-only | Fine-tuned | [bertimbau_base-C3](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C3) |
64
+ | bertimbau_base-C4 | Encoder-only | Fine-tuned | [bertimbau_base-C4](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C4) |
65
+ | bertimbau_base-C5 | Encoder-only | Fine-tuned | [bertimbau_base-C5](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_base-C5) |
66
+ | bertimbau_large-C1 | Encoder-only | Fine-tuned | [bertimbau_large-C1](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C1) |
67
+ | bertimbau_large-C2 | Encoder-only | Fine-tuned | [bertimbau_large-C2](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C2) |
68
+ | bertimbau_large-C3 | Encoder-only | Fine-tuned | [bertimbau_large-C3](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C3) |
69
+ | bertimbau_large-C4 | Encoder-only | Fine-tuned | [bertimbau_large-C4](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C4) |
70
+ | bertimbau_large-C5 | Encoder-only | Fine-tuned | [bertimbau_large-C5](https://huggingface.co/kamel-usp/jbcs2025_bertimbau_large-C5) |
71
+ | llama3-8b-C1 | Decoder-only | LoRA | [llama3-8b-C1](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C1) |
72
+ | llama3-8b-C2 | Decoder-only | LoRA | [llama3-8b-C2](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C2) |
73
+ | llama3-8b-C3 | Decoder-only | LoRA | [llama3-8b-C3](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C3) |
74
+ | llama3-8b-C4 | Decoder-only | LoRA | [llama3-8b-C4](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C4) |
75
+ | llama3-8b-C5 | Decoder-only | LoRA | [llama3-8b-C5](https://huggingface.co/kamel-usp/jbcs2025_llama3-8b-C5) |
76
+ | phi3.5-C1 | Decoder-only | LoRA | [phi3.5-C1](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C1) |
77
+ | phi3.5-C2 | Decoder-only | LoRA | [phi3.5-C2](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C2) |
78
+ | phi3.5-C3 | Decoder-only | LoRA | [phi3.5-C3](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C3) |
79
+ | phi3.5-C4 | Decoder-only | LoRA | [phi3.5-C4](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C4) |
80
+ | phi3.5-C5 | Decoder-only | LoRA | [phi3.5-C5](https://huggingface.co/kamel-usp/jbcs2025_phi3.5-C5) |
81
+ | phi4-C1 | Decoder-only | LoRA | [phi4-C1](https://huggingface.co/kamel-usp/jbcs2025_phi4-C1) |
82
+ | phi4-C2 | Decoder-only | LoRA | [phi4-C2](https://huggingface.co/kamel-usp/jbcs2025_phi4-C2) |
83
+ | phi4-C3 | Decoder-only | LoRA | [phi4-C3](https://huggingface.co/kamel-usp/jbcs2025_phi4-C3) |
84
+ | phi4-C4 | Decoder-only | LoRA | [phi4-C4](https://huggingface.co/kamel-usp/jbcs2025_phi4-C4) |
85
+ | phi4-C5 | Decoder-only | LoRA | [phi4-C5](https://huggingface.co/kamel-usp/jbcs2025_phi4-C5) |
86
+
87
+ 🧠 Additionally, **API-only models** (e.g., DeepSeek-R1, ChatGPT-4o, Sabiá-3) were evaluated but are not hosted on the Hub. Their predictions and logs are still included in this dataset.
88
+
89
+ ---
90
+
91
+ ## 🧪 How to Use this Dataset
92
+
93
+ You can easily load the data using Hugging Face datasets library:
94
+
95
+ ```python
96
+ from datasets import load_dataset
97
+ ds = load_dataset("kamel-usp/jbcs2025_experiments", split="runs")
98
+ ```
99
+
100
+ ---
101
+ ## 📄 License and Citation
102
+
103
+ This work is licensed under the [Creative Commons Attribution 4.0 International License (CC-BY-4.0)](https://creativecommons.org/licenses/by/4.0/).
104
+
105
+ If you use these artefacts, please cite our paper:
106
+
107
+ ```bibtex
108
+ TODO
109
+ ```
boostrap_confidence_intervals-00000-of-00001.parquet CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:25772cd2ca46717c6963c5015c20325ce4d1eb3083d4961ff564ef91d8e8cd59
3
- size 19082
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9aa72ad6c152f7ff95b0d1a150c3b8aed0cf91fbf169add9fd006a40786c2428
3
+ size 20808
evaluation_results-00000-of-00001.parquet CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:32e5026baa171443829d08b03c613855cdfb7ec14759c03773953e74b9297f41
3
- size 27473
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d5a70d6b2c59a80c0e284a1ce6f5bb5fce5f8fc17cb2b81d4b0f012c9a040b6f
3
+ size 30916
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C1-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.13043478260869565,51.30189136836004,0.3553525126558834,0.007246376811594235,0.1005441926494558,0.13043478260869565,0.16745801871659993,0,137,0,1,0,121,17,0,3,57,71,7,5,48,24,61,9,81,6,42,1,126,2,9,2025-07-03 09:22:09,deepseek-reasoner-zero-shot-C1-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.13043478260869565,51.30189136836004,0.3553525126558834,0.007246376811594235,0.1005441926494558,0.13043478260869565,0.16745801871659993,0,137,0,1,0,121,17,0,3,57,71,7,5,48,24,61,9,81,6,42,1,126,2,9,2025-07-03 09:22:09,deepseek-reasoner-zero-shot-C1-essay_only
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C1-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.06521739130434782,50.04345937369794,0.35261923377638793,0.0,0.037806305317826056,0.06521739130434782,0.06271081597669456,0,137,0,1,0,127,11,0,4,49,79,6,2,42,30,64,3,81,6,48,0,125,3,10,2025-07-03 16:24:10,deepseek-reasoner-zero-shot-C1-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.06521739130434782,50.04345937369794,0.35261923377638793,0.0,0.037806305317826056,0.06521739130434782,0.06271081597669456,0,137,0,1,0,127,11,0,4,49,79,6,2,42,30,64,3,81,6,48,0,125,3,10,2025-07-03 16:24:10,deepseek-reasoner-zero-shot-C1-full_context
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C2-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.21014492753623187,100.8370762270951,-0.013974764992711108,0.3840579710144928,0.1531823518212483,0.21014492753623187,0.2513227350844169,0,75,62,1,1,98,5,34,0,126,7,5,20,69,18,31,6,100,12,20,2,113,5,18,2025-07-03 14:02:04,deepseek-reasoner-zero-shot-C2-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.21014492753623187,100.8370762270951,-0.013974764992711108,0.3840579710144928,0.1531823518212483,0.21014492753623187,0.2513227350844169,0,75,62,1,1,98,5,34,0,126,7,5,20,69,18,31,6,100,12,20,2,113,5,18,2025-07-03 14:02:04,deepseek-reasoner-zero-shot-C2-essay_only
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C2-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.38405797101449274,64.78504032008749,0.41415705037996076,0.13043478260869568,0.30077552146502123,0.38405797101449274,0.34624742240946815,1,133,4,0,29,58,45,6,2,123,10,3,15,77,10,36,5,98,14,21,1,116,2,19,2025-07-03 17:00:47,deepseek-reasoner-zero-shot-C2-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.38405797101449274,64.78504032008749,0.41415705037996076,0.13043478260869568,0.30077552146502123,0.38405797101449274,0.34624742240946815,1,133,4,0,29,58,45,6,2,123,10,3,15,77,10,36,5,98,14,21,1,116,2,19,2025-07-03 17:00:47,deepseek-reasoner-zero-shot-C2-full_context
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C3-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.3695652173913043,53.405747940118566,0.38035264483627207,0.08695652173913049,0.2948667484787811,0.3695652173913043,0.32767666424014047,0,137,0,1,3,107,2,26,14,87,33,4,8,79,14,37,21,73,27,17,5,120,11,2,2025-07-03 14:31:45,deepseek-reasoner-zero-shot-C3-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.3695652173913043,53.405747940118566,0.38035264483627207,0.08695652173913049,0.2948667484787811,0.3695652173913043,0.32767666424014047,0,137,0,1,3,107,2,26,14,87,33,4,8,79,14,37,21,73,27,17,5,120,11,2,2025-07-03 14:31:45,deepseek-reasoner-zero-shot-C3-essay_only
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C3-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.47101449275362317,37.45528735338494,0.7345731998092513,0.0,0.4570540935672514,0.47101449275362317,0.46219541910331385,1,134,3,0,17,98,11,12,13,91,29,5,10,84,9,35,20,86,14,18,4,124,7,3,2025-07-03 17:23:09,deepseek-reasoner-zero-shot-C3-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.47101449275362317,37.45528735338494,0.7345731998092513,0.0,0.4570540935672514,0.47101449275362317,0.46219541910331385,1,134,3,0,17,98,11,12,13,91,29,5,10,84,9,35,20,86,14,18,4,124,7,3,2025-07-03 17:23:09,deepseek-reasoner-zero-shot-C3-full_context
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C4-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.34057971014492755,36.98805134133164,0.5167378917378918,0.0,0.25510323235234084,0.34057971014492755,0.3898373813435488,0,137,0,1,1,134,3,0,6,76,53,3,25,48,14,51,14,81,11,32,1,123,10,4,2025-07-03 14:57:27,deepseek-reasoner-zero-shot-C4-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.34057971014492755,36.98805134133164,0.5167378917378918,0.0,0.25510323235234084,0.34057971014492755,0.3898373813435488,0,137,0,1,1,134,3,0,6,76,53,3,25,48,14,51,14,81,11,32,1,123,10,4,2025-07-03 14:57:27,deepseek-reasoner-zero-shot-C4-essay_only
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C4-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.3115942028985507,38.06934938134405,0.4917800954569559,0.0,0.20492171227465347,0.3115942028985507,0.36490748287423475,0,137,0,1,1,132,5,0,5,71,58,4,23,44,18,53,14,84,8,32,0,127,6,5,2025-07-03 17:53:15,deepseek-reasoner-zero-shot-C4-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.3115942028985507,38.06934938134405,0.4917800954569559,0.0,0.20492171227465347,0.3115942028985507,0.36490748287423475,0,137,0,1,1,132,5,0,5,71,58,4,23,44,18,53,14,84,8,32,0,127,6,5,2025-07-03 17:53:15,deepseek-reasoner-zero-shot-C4-full_context
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C5-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.427536231884058,54.26718655165278,0.550084715305232,0.07971014492753625,0.37133655394524956,0.427536231884058,0.42565987537632144,17,110,6,5,14,83,23,18,9,93,21,15,8,98,15,17,11,94,12,21,0,133,2,3,2025-07-03 15:54:55,deepseek-reasoner-zero-shot-C5-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.427536231884058,54.26718655165278,0.550084715305232,0.07971014492753625,0.37133655394524956,0.427536231884058,0.42565987537632144,17,110,6,5,14,83,23,18,9,93,21,15,8,98,15,17,11,94,12,21,0,133,2,3,2025-07-03 15:54:55,deepseek-reasoner-zero-shot-C5-essay_only
runs/api_models/deepseek-r1/deepseek-reasoner-zero-shot-C5-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.4057971014492754,53.622405007986906,0.5808348030570252,0.07246376811594202,0.389267558875402,0.4057971014492754,0.4032936846236078,19,106,10,3,13,83,23,19,5,89,25,19,6,99,14,19,12,99,7,20,1,132,3,2,2025-07-03 18:16:40,deepseek-reasoner-zero-shot-C5-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.4057971014492754,53.622405007986906,0.5808348030570252,0.07246376811594202,0.389267558875402,0.4057971014492754,0.4032936846236078,19,106,10,3,13,83,23,19,5,89,25,19,6,99,14,19,12,99,7,20,1,132,3,2,2025-07-03 18:16:40,deepseek-reasoner-zero-shot-C5-full_context
runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/.hydra/config.yaml ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ cache_dir: /tmp/
2
+ dataset:
3
+ name: kamel-usp/aes_enem_dataset
4
+ split: JBCS2025
5
+ training_params:
6
+ seed: 42
7
+ num_train_epochs: 20
8
+ logging_steps: 100
9
+ metric_for_best_model: QWK
10
+ bf16: true
11
+ bootstrap:
12
+ enabled: true
13
+ n_bootstrap: 10000
14
+ bootstrap_seed: 42
15
+ metrics:
16
+ - QWK
17
+ - Macro_F1
18
+ - Weighted_F1
19
+ post_training_results:
20
+ model_path: /workspace/jbcs2025/outputs/2025-03-24/20-42-59
21
+ experiments:
22
+ model:
23
+ name: gpt-4o-2024-11-20
24
+ type: openai_chatgpt_4o
25
+ api_url: https://api.openai.com/v1
26
+ prompt_type: zero-shot
27
+ use_essay_prompt: false
28
+ temperature: 0.1
29
+ max_tokens: 12000
30
+ seed: 42
31
+ number_repetition_eval: 10
32
+ dataset:
33
+ grade_index: 4
34
+ use_full_context: false
35
+ training_id: gpt4-graderPrompt-zero-shot-C5
runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/.hydra/hydra.yaml ADDED
@@ -0,0 +1,155 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ hydra:
2
+ run:
3
+ dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
4
+ sweep:
5
+ dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
6
+ subdir: ${hydra.job.num}
7
+ launcher:
8
+ _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
9
+ sweeper:
10
+ _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
11
+ max_batch_size: null
12
+ params: null
13
+ help:
14
+ app_name: ${hydra.job.name}
15
+ header: '${hydra.help.app_name} is powered by Hydra.
16
+
17
+ '
18
+ footer: 'Powered by Hydra (https://hydra.cc)
19
+
20
+ Use --hydra-help to view Hydra specific help
21
+
22
+ '
23
+ template: '${hydra.help.header}
24
+
25
+ == Configuration groups ==
26
+
27
+ Compose your configuration from those groups (group=option)
28
+
29
+
30
+ $APP_CONFIG_GROUPS
31
+
32
+
33
+ == Config ==
34
+
35
+ Override anything in the config (foo.bar=value)
36
+
37
+
38
+ $CONFIG
39
+
40
+
41
+ ${hydra.help.footer}
42
+
43
+ '
44
+ hydra_help:
45
+ template: 'Hydra (${hydra.runtime.version})
46
+
47
+ See https://hydra.cc for more info.
48
+
49
+
50
+ == Flags ==
51
+
52
+ $FLAGS_HELP
53
+
54
+
55
+ == Configuration groups ==
56
+
57
+ Compose your configuration from those groups (For example, append hydra/job_logging=disabled
58
+ to command line)
59
+
60
+
61
+ $HYDRA_CONFIG_GROUPS
62
+
63
+
64
+ Use ''--cfg hydra'' to Show the Hydra config.
65
+
66
+ '
67
+ hydra_help: ???
68
+ hydra_logging:
69
+ version: 1
70
+ formatters:
71
+ simple:
72
+ format: '[%(asctime)s][HYDRA] %(message)s'
73
+ handlers:
74
+ console:
75
+ class: logging.StreamHandler
76
+ formatter: simple
77
+ stream: ext://sys.stdout
78
+ root:
79
+ level: INFO
80
+ handlers:
81
+ - console
82
+ loggers:
83
+ logging_example:
84
+ level: DEBUG
85
+ disable_existing_loggers: false
86
+ job_logging:
87
+ version: 1
88
+ formatters:
89
+ simple:
90
+ format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
91
+ handlers:
92
+ console:
93
+ class: logging.StreamHandler
94
+ formatter: simple
95
+ stream: ext://sys.stdout
96
+ file:
97
+ class: logging.FileHandler
98
+ formatter: simple
99
+ filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
100
+ root:
101
+ level: INFO
102
+ handlers:
103
+ - console
104
+ - file
105
+ disable_existing_loggers: false
106
+ env: {}
107
+ mode: RUN
108
+ searchpath: []
109
+ callbacks: {}
110
+ output_subdir: .hydra
111
+ overrides:
112
+ hydra:
113
+ - hydra.mode=RUN
114
+ task: []
115
+ job:
116
+ name: run_inference_experiment
117
+ chdir: null
118
+ override_dirname: ''
119
+ id: ???
120
+ num: ???
121
+ config_name: config
122
+ env_set: {}
123
+ env_copy: []
124
+ config:
125
+ override_dirname:
126
+ kv_sep: '='
127
+ item_sep: ','
128
+ exclude_keys: []
129
+ runtime:
130
+ version: 1.3.2
131
+ version_base: '1.1'
132
+ cwd: C:\Users\Igor\Documents\jbcs2025-u-andrebarbosa-fix-improve-api-calls
133
+ config_sources:
134
+ - path: hydra.conf
135
+ schema: pkg
136
+ provider: hydra
137
+ - path: C:\Users\Igor\Documents\jbcs2025-u-andrebarbosa-fix-improve-api-calls\configs
138
+ schema: file
139
+ provider: main
140
+ - path: ''
141
+ schema: structured
142
+ provider: schema
143
+ output_dir: C:\Users\Igor\Documents\jbcs2025-u-andrebarbosa-fix-improve-api-calls\outputs\2025-07-06\12-29-03
144
+ choices:
145
+ experiments: api_models_llm/C5
146
+ hydra/env: default
147
+ hydra/callbacks: null
148
+ hydra/job_logging: default
149
+ hydra/hydra_logging: default
150
+ hydra/hydra_help: default
151
+ hydra/help: default
152
+ hydra/sweeper: basic
153
+ hydra/launcher: basic
154
+ hydra/output: default
155
+ verbose: false
runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/.hydra/overrides.yaml ADDED
@@ -0,0 +1 @@
 
 
1
+ []
runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/bootstrap_confidence_intervals.csv ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ experiment_id,timestamp,QWK_mean,QWK_lower_95ci,QWK_upper_95ci,QWK_ci_width,Macro_F1_mean,Macro_F1_lower_95ci,Macro_F1_upper_95ci,Macro_F1_ci_width,Weighted_F1_mean,Weighted_F1_lower_95ci,Weighted_F1_upper_95ci,Weighted_F1_ci_width
2
+ gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only,2025-07-06 12:29:03,0.5373181242424607,0.4053118113144384,0.6570192510903595,0.25170743977592114,0.31811780692889746,0.24970444329152286,0.39021736857518213,0.14051292528365927,0.3387106239456289,0.25803940648998425,0.42196442581330057,0.16392501932331632
runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/evaluation_results.csv ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.34057971014492755,59.8548970064453,0.5415725988518352,0.08695652173913049,0.3225370722321942,0.34057971014492755,0.3391178104327627,17,111,5,5,14,70,36,18,2,95,19,22,3,105,8,22,9,99,7,23,2,119,16,1,2025-07-06 12:29:03,gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only
runs/{slm_decoder_models/phi-4/jbcs2025_phi-4-phi4_classification_lora-C5-full_context-phi4_classification_lora-C5-full_context/jbcs2025_phi-4-phi4_classification_lora-C5-full_context-phi4_classification_lora-C5-full_context_inference_results.jsonl → api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only_inference_results.jsonl} RENAMED
The diff for this file is too large to render. See raw diff
 
runs/api_models/gpt-4o/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only/run_inference_experiment.log ADDED
The diff for this file is too large to render. See raw diff
 
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C1-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.35507246376811596,45.809941329777764,0.5084038575083645,0.007246376811594235,0.19888347813976495,0.35507246376811596,0.4240888729157106,0,137,0,1,0,102,36,0,1,108,20,9,22,53,19,44,25,76,11,26,1,125,3,9,2025-07-02 20:39:39,gpt-4o-2024-11-20-zero-shot-C1-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.35507246376811596,45.809941329777764,0.5084038575083645,0.007246376811594235,0.19888347813976495,0.35507246376811596,0.4240888729157106,0,137,0,1,0,102,36,0,1,108,20,9,22,53,19,44,25,76,11,26,1,125,3,9,2025-07-02 20:39:39,gpt-4o-2024-11-20-zero-shot-C1-essay_only
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C1-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.36231884057971014,45.17277620586239,0.47884301776671523,0.01449275362318836,0.18382738455333736,0.36231884057971014,0.4198216681133118,0,137,0,1,0,108,30,0,2,102,26,8,22,50,22,44,26,77,10,25,0,128,0,10,2025-07-02 19:00:34,gpt-4o-2024-11-20-zero-shot-C1-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.36231884057971014,45.17277620586239,0.47884301776671523,0.01449275362318836,0.18382738455333736,0.36231884057971014,0.4198216681133118,0,137,0,1,0,108,30,0,2,102,26,8,22,50,22,44,26,77,10,25,0,128,0,10,2025-07-02 19:00:34,gpt-4o-2024-11-20-zero-shot-C1-full_context
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C2-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.2463768115942029,84.44190181781019,0.2004409021536374,0.24637681159420288,0.17546152518978606,0.2463768115942029,0.2565616842200018,0,122,15,1,11,53,50,24,0,132,1,5,11,80,7,40,3,106,6,23,9,93,25,11,2025-07-02 20:45:57,gpt-4o-2024-11-20-zero-shot-C2-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.2463768115942029,84.44190181781019,0.2004409021536374,0.24637681159420288,0.17546152518978606,0.2463768115942029,0.2565616842200018,0,122,15,1,11,53,50,24,0,132,1,5,11,80,7,40,3,106,6,23,9,93,25,11,2025-07-02 20:45:57,gpt-4o-2024-11-20-zero-shot-C2-essay_only
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C2-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.43478260869565216,56.465970257327996,0.511394360757049,0.050724637681159424,0.3838206627680312,0.43478260869565216,0.4091956945503856,1,134,3,0,17,79,24,18,2,128,5,3,27,57,30,24,2,110,2,24,11,104,14,9,2025-07-02 19:10:24,gpt-4o-2024-11-20-zero-shot-C2-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.43478260869565216,56.465970257327996,0.511394360757049,0.050724637681159424,0.3838206627680312,0.43478260869565216,0.4091956945503856,1,134,3,0,17,79,24,18,2,128,5,3,27,57,30,24,2,110,2,24,11,104,14,9,2025-07-02 19:10:24,gpt-4o-2024-11-20-zero-shot-C2-full_context
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C3-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.3333333333333333,50.504699164346675,0.3833028641072517,0.04347826086956519,0.23851576330962254,0.3333333333333333,0.2866639331395247,0,137,0,1,0,109,0,29,16,83,37,2,14,66,27,31,13,85,15,25,3,118,13,4,2025-07-02 20:55:50,gpt-4o-2024-11-20-zero-shot-C3-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.3333333333333333,50.504699164346675,0.3833028641072517,0.04347826086956519,0.23851576330962254,0.3333333333333333,0.2866639331395247,0,137,0,1,0,109,0,29,16,83,37,2,14,66,27,31,13,85,15,25,3,118,13,4,2025-07-02 20:55:50,gpt-4o-2024-11-20-zero-shot-C3-essay_only
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C3-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.3333333333333333,43.33890711087691,0.5317330652255876,0.01449275362318836,0.25460603031817425,0.3333333333333333,0.28915252518668205,0,137,0,1,0,109,0,29,14,82,38,4,14,65,28,31,14,83,17,24,4,122,9,3,2025-07-02 19:44:08,gpt-4o-2024-11-20-zero-shot-C3-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.3333333333333333,43.33890711087691,0.5317330652255876,0.01449275362318836,0.25460603031817425,0.3333333333333333,0.28915252518668205,0,137,0,1,0,109,0,29,14,82,38,4,14,65,28,31,14,83,17,24,4,122,9,3,2025-07-02 19:44:08,gpt-4o-2024-11-20-zero-shot-C3-full_context
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C4-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.35507246376811596,38.52347298744614,0.5053763440860215,0.0,0.2769126269126269,0.35507246376811596,0.3919537549972333,0,137,0,1,1,134,3,0,8,83,46,1,22,49,13,54,16,82,10,30,2,116,17,3,2025-07-02 21:01:59,gpt-4o-2024-11-20-zero-shot-C4-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.35507246376811596,38.52347298744614,0.5053763440860215,0.0,0.2769126269126269,0.35507246376811596,0.3919537549972333,0,137,0,1,1,134,3,0,8,83,46,1,22,49,13,54,16,82,10,30,2,116,17,3,2025-07-02 21:01:59,gpt-4o-2024-11-20-zero-shot-C4-essay_only
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C4-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.3333333333333333,40.28881241482679,0.49098956686689854,0.0,0.24141879625750592,0.3333333333333333,0.36650455668688486,0,137,0,1,1,132,5,0,8,91,38,1,24,50,12,52,11,79,13,35,2,109,24,3,2025-07-02 20:02:02,gpt-4o-2024-11-20-zero-shot-C4-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.3333333333333333,40.28881241482679,0.49098956686689854,0.0,0.24141879625750592,0.3333333333333333,0.36650455668688486,0,137,0,1,1,132,5,0,8,91,38,1,24,50,12,52,11,79,13,35,2,109,24,3,2025-07-02 20:02:02,gpt-4o-2024-11-20-zero-shot-C4-full_context
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C5-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.3188405797101449,60.048289746247356,0.5487540742298391,0.07971014492753625,0.2921402969790066,0.3188405797101449,0.29828469022017406,16,112,4,6,13,81,25,19,3,96,18,21,10,92,21,15,0,106,0,32,2,109,26,1,2025-07-02 21:08:07,gpt-4o-2024-11-20-zero-shot-C5-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.3188405797101449,60.048289746247356,0.5487540742298391,0.07971014492753625,0.2921402969790066,0.3188405797101449,0.29828469022017406,16,112,4,6,13,81,25,19,3,96,18,21,10,92,21,15,0,106,0,32,2,109,26,1,2025-07-02 21:08:07,gpt-4o-2024-11-20-zero-shot-C5-essay_only
runs/{slm_decoder_models/phi-3.5/jbcs2025_Phi-3.5-mini-instruct-phi35_classification_lora-C5-full_context-phi35_classification_lora-C5-full_context/jbcs2025_Phi-3.5-mini-instruct-phi35_classification_lora-C5-full_context-phi35_classification_lora-C5-full_context_inference_results.jsonl → api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C5-essay_only/gpt-4o-2024-11-20-grader-zero-shot-C5-essay_only_inference_results.jsonl} RENAMED
The diff for this file is too large to render. See raw diff
 
runs/api_models/gpt-4o/gpt-4o-2024-11-20-zero-shot-C5-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.18115942028985507,74.6003846592251,0.3516814782915084,0.1376811594202898,0.17063864552913363,0.18115942028985507,0.18542501798746017,2,116,0,20,9,75,31,23,5,95,19,19,5,92,21,20,2,106,0,30,2,93,42,1,2025-07-02 20:20:08,gpt-4o-2024-11-20-zero-shot-C5-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.18115942028985507,74.6003846592251,0.3516814782915084,0.1376811594202898,0.17063864552913363,0.18115942028985507,0.18542501798746017,2,116,0,20,9,75,31,23,5,95,19,19,5,92,21,20,2,106,0,30,2,93,42,1,2025-07-02 20:20:08,gpt-4o-2024-11-20-zero-shot-C5-full_context
runs/api_models/sabia-3/sabia-3-zero-shot-C1-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.6666666666666666,25.252349582173338,0.6850361025811271,0.0,0.322920439158877,0.6666666666666666,0.6618478065817089,0,137,0,1,0,132,6,0,3,121,7,7,54,53,19,12,34,74,13,17,1,127,1,9,2025-07-02 16:22:36,sabia-3-zero-shot-C1-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.6666666666666666,25.252349582173338,0.6850361025811271,0.0,0.322920439158877,0.6666666666666666,0.6618478065817089,0,137,0,1,0,132,6,0,3,121,7,7,54,53,19,12,34,74,13,17,1,127,1,9,2025-07-02 16:22:36,sabia-3-zero-shot-C1-essay_only
runs/api_models/sabia-3/sabia-3-zero-shot-C1-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.6159420289855072,28.691260094270895,0.5724757832271576,0.0,0.32370149407422427,0.6159420289855072,0.6025341297513271,0,137,0,1,0,136,2,0,7,115,13,3,52,44,28,14,25,77,10,26,1,128,0,9,2025-07-02 16:52:00,sabia-3-zero-shot-C1-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.6159420289855072,28.691260094270895,0.5724757832271576,0.0,0.32370149407422427,0.6159420289855072,0.6025341297513271,0,137,0,1,0,136,2,0,7,115,13,3,52,44,28,14,25,77,10,26,1,128,0,9,2025-07-02 16:52:00,sabia-3-zero-shot-C1-full_context
runs/api_models/sabia-3/sabia-3-zero-shot-C2-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.14492753623188406,109.33262636745629,0.017322116779246777,0.49275362318840576,0.0822477650063857,0.14492753623188406,0.1083426540697905,1,76,61,0,17,50,53,18,0,133,0,5,0,85,2,51,2,111,1,24,0,117,1,20,2025-07-02 16:31:52,sabia-3-zero-shot-C2-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.14492753623188406,109.33262636745629,0.017322116779246777,0.49275362318840576,0.0822477650063857,0.14492753623188406,0.1083426540697905,1,76,61,0,17,50,53,18,0,133,0,5,0,85,2,51,2,111,1,24,0,117,1,20,2025-07-02 16:31:52,sabia-3-zero-shot-C2-essay_only
runs/api_models/sabia-3/sabia-3-zero-shot-C2-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.42028985507246375,54.48041796855991,0.4599156118143459,0.05797101449275366,0.31263464650838124,0.42028985507246375,0.4044300660220312,1,134,3,0,17,88,15,18,0,126,7,5,31,53,34,20,7,96,16,19,2,113,5,18,2025-07-02 17:35:43,sabia-3-zero-shot-C2-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.42028985507246375,54.48041796855991,0.4599156118143459,0.05797101449275366,0.31263464650838124,0.42028985507246375,0.4044300660220312,1,134,3,0,17,88,15,18,0,126,7,5,31,53,34,20,7,96,16,19,2,113,5,18,2025-07-02 17:35:43,sabia-3-zero-shot-C2-full_context
runs/api_models/sabia-3/sabia-3-zero-shot-C3-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.35507246376811596,54.90439648719571,0.30001170548987466,0.08695652173913049,0.2182826527105678,0.35507246376811596,0.29550539313795443,0,137,0,1,0,109,0,29,2,110,10,16,31,51,42,14,11,82,18,27,5,112,19,2,2025-07-02 16:36:17,sabia-3-zero-shot-C3-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.35507246376811596,54.90439648719571,0.30001170548987466,0.08695652173913049,0.2182826527105678,0.35507246376811596,0.29550539313795443,0,137,0,1,0,109,0,29,2,110,10,16,31,51,42,14,11,82,18,27,5,112,19,2,2025-07-02 16:36:17,sabia-3-zero-shot-C3-essay_only
runs/api_models/sabia-3/sabia-3-zero-shot-C3-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.2971014492753623,46.43836494893457,0.45076389780459625,0.007246376811594235,0.22956713983978905,0.2971014492753623,0.21865954521600722,1,134,3,0,0,109,0,29,4,110,10,14,32,33,60,13,2,89,11,36,2,118,13,5,2025-07-02 17:43:28,sabia-3-zero-shot-C3-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.2971014492753623,46.43836494893457,0.45076389780459625,0.007246376811594235,0.22956713983978905,0.2971014492753623,0.21865954521600722,1,134,3,0,0,109,0,29,4,110,10,14,32,33,60,13,2,89,11,36,2,118,13,5,2025-07-02 17:43:28,sabia-3-zero-shot-C3-full_context
runs/api_models/sabia-3/sabia-3-zero-shot-C4-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.5362318840579711,31.39278971956477,0.5190651906519066,0.0,0.2860954930834449,0.5362318840579711,0.5241443898437088,0,137,0,1,1,132,5,0,3,116,13,6,58,30,32,18,11,86,6,35,1,125,8,4,2025-07-02 16:40:55,sabia-3-zero-shot-C4-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.5362318840579711,31.39278971956477,0.5190651906519066,0.0,0.2860954930834449,0.5362318840579711,0.5241443898437088,0,137,0,1,1,132,5,0,3,116,13,6,58,30,32,18,11,86,6,35,1,125,8,4,2025-07-02 16:40:55,sabia-3-zero-shot-C4-essay_only
runs/api_models/sabia-3/sabia-3-zero-shot-C4-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.4927536231884058,32.48187900611841,0.38747439274217144,0.0,0.254320987654321,0.4927536231884058,0.42893183038110577,0,137,0,1,1,134,3,0,5,113,16,4,58,16,46,18,4,88,4,42,0,132,1,5,2025-07-02 18:38:18,sabia-3-zero-shot-C4-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.4927536231884058,32.48187900611841,0.38747439274217144,0.0,0.254320987654321,0.4927536231884058,0.42893183038110577,0,137,0,1,1,134,3,0,5,113,16,4,58,16,46,18,4,88,4,42,0,132,1,5,2025-07-02 18:38:18,sabia-3-zero-shot-C4-full_context
runs/api_models/sabia-3/sabia-3-zero-shot-C5-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.3188405797101449,63.519938670433646,0.5108775360547543,0.1159420289855072,0.29973525260410505,0.3188405797101449,0.34422621147496424,13,111,5,9,9,92,14,23,4,109,5,20,7,84,29,18,11,86,20,21,0,114,21,3,2025-07-02 16:45:09,sabia-3-zero-shot-C5-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.3188405797101449,63.519938670433646,0.5108775360547543,0.1159420289855072,0.29973525260410505,0.3188405797101449,0.34422621147496424,13,111,5,9,9,92,14,23,4,109,5,20,7,84,29,18,11,86,20,21,0,114,21,3,2025-07-02 16:45:09,sabia-3-zero-shot-C5-essay_only
runs/api_models/sabia-3/sabia-3-zero-shot-C5-full_context/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.26811594202898553,61.19581306128618,0.5346890201891559,0.09420289855072461,0.27142278219864424,0.26811594202898553,0.28162040774484554,6,112,4,16,8,82,24,24,5,104,10,19,6,86,27,19,9,93,13,23,3,112,23,0,2025-07-02 18:45:35,sabia-3-zero-shot-C5-full_context
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.26811594202898553,61.19581306128618,0.5346890201891559,0.09420289855072461,0.27142278219864424,0.26811594202898553,0.28162040774484554,6,112,4,16,8,82,24,24,5,104,10,19,6,86,27,19,9,93,13,23,3,112,23,0,2025-07-02 18:45:35,sabia-3-zero-shot-C5-full_context
runs/base_models/bertimbau/jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.644927536231884,26.37521893583148,0.6742722265932337,0.007246376811594235,0.44138845418188133,0.644927536231884,0.6413771139990777,0,137,0,1,0,138,0,0,5,123,5,5,56,52,20,10,22,79,8,29,6,112,16,4,2025-06-30 23:51:41,jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.644927536231884,26.37521893583148,0.6742722265932337,0.007246376811594235,0.44138845418188133,0.644927536231884,0.6413771139990777,0,137,0,1,0,138,0,0,5,123,5,5,56,52,20,10,22,79,8,29,6,112,16,4,2025-06-30 23:51:41,jbcs2025_bertimbau_base-C1-encoder_classification-C1-essay_only
runs/base_models/bertimbau/jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.37681159420289856,55.32512598464997,0.4220445459737294,0.06521739130434778,0.2801049472150572,0.37681159420289856,0.38226236003582026,0,137,0,1,13,90,13,22,3,112,21,2,25,56,31,26,5,99,13,21,6,110,8,14,2025-06-30 23:53:32,jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.37681159420289856,55.32512598464997,0.4220445459737294,0.06521739130434778,0.2801049472150572,0.37681159420289856,0.38226236003582026,0,137,0,1,13,90,13,22,3,112,21,2,25,56,31,26,5,99,13,21,6,110,8,14,2025-06-30 23:53:32,jbcs2025_bertimbau_base-C2-encoder_classification-C2-essay_only
runs/base_models/bertimbau/jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.37681159420289856,52.64042641120627,0.3452054794520547,0.09420289855072461,0.25943499029705924,0.37681159420289856,0.33380294701134283,0,137,0,1,0,109,0,29,13,101,19,5,20,71,22,25,17,67,33,21,2,119,12,5,2025-06-30 23:55:38,jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.37681159420289856,52.64042641120627,0.3452054794520547,0.09420289855072461,0.25943499029705924,0.37681159420289856,0.33380294701134283,0,137,0,1,0,109,0,29,13,101,19,5,20,71,22,25,17,67,33,21,2,119,12,5,2025-06-30 23:55:38,jbcs2025_bertimbau_base-C3-encoder_classification-C3-essay_only
runs/base_models/bertimbau/jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.644927536231884,26.37521893583148,0.6258134490238612,0.007246376811594235,0.36114488348530904,0.644927536231884,0.6545879036165807,0,137,0,1,0,137,0,1,5,118,11,4,51,49,13,25,30,74,18,16,3,126,7,2,2025-06-30 23:57:45,jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.644927536231884,26.37521893583148,0.6258134490238612,0.007246376811594235,0.36114488348530904,0.644927536231884,0.6545879036165807,0,137,0,1,0,137,0,1,5,118,11,4,51,49,13,25,30,74,18,16,3,126,7,2,2025-06-30 23:57:45,jbcs2025_bertimbau_base-C4-encoder_classification-C4-essay_only
runs/base_models/bertimbau/jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.3188405797101449,61.2904702146299,0.476219483623073,0.13043478260869568,0.2055897809038726,0.3188405797101449,0.25808413038205613,3,113,3,19,9,71,35,23,3,103,11,21,1,108,5,24,28,66,40,4,0,135,0,3,2025-06-30 23:59:55,jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.3188405797101449,61.2904702146299,0.476219483623073,0.13043478260869568,0.2055897809038726,0.3188405797101449,0.25808413038205613,3,113,3,19,9,71,35,23,3,103,11,21,1,108,5,24,28,66,40,4,0,135,0,3,2025-06-30 23:59:55,jbcs2025_bertimbau_base-C5-encoder_classification-C5-essay_only
runs/base_models/mbert/jbcs2025_mbert_base-C1-encoder_classification-C1-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.5362318840579711,30.072376462244492,0.4505920783993467,0.007246376811594235,0.3244639912039582,0.5362318840579711,0.518137852459147,0,137,0,1,0,138,0,0,5,123,5,5,42,44,28,24,27,58,29,24,0,126,2,10,2025-07-01 01:04:58,jbcs2025_mbert_base-C1-encoder_classification-C1-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.5362318840579711,30.072376462244492,0.4505920783993467,0.007246376811594235,0.3244639912039582,0.5362318840579711,0.518137852459147,0,137,0,1,0,138,0,0,5,123,5,5,42,44,28,24,27,58,29,24,0,126,2,10,2025-07-01 01:04:58,jbcs2025_mbert_base-C1-encoder_classification-C1-essay_only
runs/base_models/mbert/jbcs2025_mbert_base-C2-encoder_classification-C2-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.36231884057971014,62.78557943912954,0.14498141263940523,0.08695652173913049,0.22145597726993074,0.36231884057971014,0.3182603637608693,0,137,0,1,5,88,15,30,1,130,3,4,32,41,46,19,12,94,18,14,0,112,6,20,2025-07-01 01:07:16,jbcs2025_mbert_base-C2-encoder_classification-C2-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.36231884057971014,62.78557943912954,0.14498141263940523,0.08695652173913049,0.22145597726993074,0.36231884057971014,0.3182603637608693,0,137,0,1,5,88,15,30,1,130,3,4,32,41,46,19,12,94,18,14,0,112,6,20,2025-07-01 01:07:16,jbcs2025_mbert_base-C2-encoder_classification-C2-essay_only
runs/base_models/mbert/jbcs2025_mbert_base-C3-encoder_classification-C3-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.2318840579710145,60.24106163777641,0.2641316569559441,0.09420289855072461,0.15672242946179116,0.2318840579710145,0.1613437300185681,0,137,0,1,0,109,0,29,15,57,63,3,1,92,1,44,12,80,20,26,4,109,22,3,2025-07-01 01:09:31,jbcs2025_mbert_base-C3-encoder_classification-C3-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.2318840579710145,60.24106163777641,0.2641316569559441,0.09420289855072461,0.15672242946179116,0.2318840579710145,0.1613437300185681,0,137,0,1,0,109,0,29,15,57,63,3,1,92,1,44,12,80,20,26,4,109,22,3,2025-07-01 01:09:31,jbcs2025_mbert_base-C3-encoder_classification-C3-essay_only
runs/base_models/mbert/jbcs2025_mbert_base-C4-encoder_classification-C4-essay_only/evaluation_results.csv CHANGED
@@ -1,2 +1,2 @@
1
- accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
- 0.5,33.70803886401538,0.28170809432759725,0.007246376811594235,0.17299898682877404,0.5,0.4091229461257213,0,137,0,1,0,137,0,1,0,129,0,9,64,14,48,12,2,84,8,44,3,120,13,2,2025-07-01 01:11:45,jbcs2025_mbert_base-C4-encoder_classification-C4-essay_only
 
1
+ accuracy,RMSE,QWK,HDIV,Macro_F1,Micro_F1,Weighted_F1,TP_0,TN_0,FP_0,FN_0,TP_1,TN_1,FP_1,FN_1,TP_2,TN_2,FP_2,FN_2,TP_3,TN_3,FP_3,FN_3,TP_4,TN_4,FP_4,FN_4,TP_5,TN_5,FP_5,FN_5,timestamp,id
2
+ 0.5,33.70803886401538,0.28170809432759725,0.007246376811594235,0.17299898682877404,0.5,0.4091229461257213,0,137,0,1,0,137,0,1,0,129,0,9,64,14,48,12,2,84,8,44,3,120,13,2,2025-07-01 01:11:45,jbcs2025_mbert_base-C4-encoder_classification-C4-essay_only