File size: 2,012 Bytes
9debe22
 
 
 
 
 
6aab4e6
9debe22
 
 
 
 
 
 
 
 
 
 
 
d7f0e34
 
9debe22
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d7f0e34
9debe22
 
 
 
 
d7f0e34
 
 
 
 
 
 
 
 
 
9debe22
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: distilbert-base-multilingual-cased
model-index:
- name: distilbert-base-cased-distilled-emotion-bg
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert-base-cased-distilled-emotion-bg

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5784
- Accuracy: 0.8061

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3346        | 1.0   | 187  | 1.0077          | 0.6036   |
| 0.763         | 2.0   | 374  | 0.6359          | 0.7868   |
| 0.4931        | 3.0   | 561  | 0.5821          | 0.8008   |
| 0.3635        | 4.0   | 748  | 0.5784          | 0.8061   |
| 0.2724        | 5.0   | 935  | 0.5829          | 0.8189   |
| 0.2116        | 6.0   | 1122 | 0.5872          | 0.8168   |
| 0.1684        | 7.0   | 1309 | 0.6480          | 0.8148   |
| 0.1336        | 8.0   | 1496 | 0.6630          | 0.8122   |
| 0.112         | 9.0   | 1683 | 0.6836          | 0.8222   |
| 0.0966        | 10.0  | 1870 | 0.6859          | 0.8202   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2