End of training

README.md

@@ -11,8 +11,6 @@ metrics:
 model-index:
 - name: flan-t5-small-hallucination-text-classification
   results: []
-datasets:
-- cemuluoglakci/hallucination_acceptance_agent_instruction_dataset
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -20,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # flan-t5-small-hallucination-text-classification
 
-This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the Hallucination Acceptance Agent Instruction dataset.
+This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6364
-- Precision: 0.7374
-- Recall: 0.7420
-- F1: 0.7370
-- Accuracy: 0.7420
+- Loss: 0.6695
+- Precision: 0.7097
+- Recall: 0.7129
+- F1: 0.7034
+- Accuracy: 0.7129
 
 ## Model description
 
@@ -46,26 +44,18 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0003
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 2
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.9155        | 0.2008 | 100  | 0.8142          | 0.6260    | 0.6365 | 0.6213 | 0.6365   |
-| 0.777         | 0.4016 | 200  | 0.7090          | 0.7062    | 0.7098 | 0.7003 | 0.7098   |
-| 0.7625        | 0.6024 | 300  | 0.6595          | 0.7365    | 0.7299 | 0.7212 | 0.7299   |
-| 0.7136        | 0.8032 | 400  | 0.7185          | 0.7084    | 0.7108 | 0.7090 | 0.7108   |
-| 0.6807        | 1.0040 | 500  | 0.7207          | 0.7216    | 0.7008 | 0.7066 | 0.7008   |
-| 0.6522        | 1.2048 | 600  | 0.6221          | 0.7340    | 0.7329 | 0.7321 | 0.7329   |
-| 0.6355        | 1.4056 | 700  | 0.6216          | 0.7358    | 0.7400 | 0.7368 | 0.7400   |
-| 0.6074        | 1.6064 | 800  | 0.6261          | 0.7463    | 0.7490 | 0.7462 | 0.7490   |
-| 0.5999        | 1.8072 | 900  | 0.6364          | 0.7374    | 0.7420 | 0.7370 | 0.7420   |
+| 0.827         | 0.8032 | 200  | 0.6695          | 0.7097    | 0.7129 | 0.7034 | 0.7129   |
 
 
 ### Framework versions
@@ -73,4 +63,4 @@ The following hyperparameters were used during training:
 - Transformers 4.41.2
 - Pytorch 2.3.0+cu121
 - Datasets 2.19.1
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1

model.safetensors

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runs/Jun01_14-34-21_b5a25765b253/events.out.tfevents.1717253446.b5a25765b253.9583.3

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training_args.bin

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