File size: 2,061 Bytes
3ed8dd5
 
65ccbaa
 
 
 
 
3ed8dd5
65ccbaa
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: fine-tune-vanilla-bert-base-uncased-ch9
  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. -->

# fine-tune-vanilla-bert-base-uncased-ch9

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1877
- Micro f1: 0.7208
- Macro f1: 0.6293

## 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: 4
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Micro f1 | Macro f1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.4535        | 1.0   | 56   | 0.3607          | 0.0      | 0.0      |
| 0.3388        | 2.0   | 112  | 0.3270          | 0.0      | 0.0      |
| 0.3023        | 3.0   | 168  | 0.2794          | 0.4654   | 0.2139   |
| 0.2515        | 4.0   | 224  | 0.2420          | 0.4750   | 0.1855   |
| 0.2095        | 5.0   | 280  | 0.2263          | 0.5318   | 0.2599   |
| 0.1673        | 6.0   | 336  | 0.2135          | 0.6429   | 0.4327   |
| 0.1424        | 7.0   | 392  | 0.1885          | 0.6631   | 0.4890   |
| 0.1049        | 8.0   | 448  | 0.1801          | 0.7164   | 0.6139   |
| 0.08          | 9.0   | 504  | 0.1802          | 0.7136   | 0.6020   |
| 0.0637        | 10.0  | 560  | 0.1877          | 0.7208   | 0.6293   |


### Framework versions

- Transformers 4.16.2
- Pytorch 2.1.0+cu118
- Datasets 1.16.1
- Tokenizers 0.15.0