File size: 2,555 Bytes
02c86bc
 
 
 
 
 
5327d13
02c86bc
 
 
 
 
 
 
 
 
 
 
 
75f2155
 
02c86bc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
75f2155
02c86bc
 
 
75f2155
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
02c86bc
 
 
 
 
 
 
 
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
71
72
73
74
75
76
77
78
79
80
81
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
base_model: distilroberta-base
model-index:
- name: distilroberta-base-finegrain
  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. -->

# distilroberta-base-finegrain

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3713
- F1: 0.9129

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.3944        | 1.0   | 844   | 0.3998          | 0.9163 |
| 0.3886        | 2.0   | 1688  | 0.4020          | 0.9163 |
| 0.3899        | 3.0   | 2532  | 0.3423          | 0.9163 |
| 0.4026        | 4.0   | 3376  | 0.3837          | 0.9163 |
| 0.3911        | 5.0   | 4220  | 0.3492          | 0.9163 |
| 0.3856        | 6.0   | 5064  | 0.3504          | 0.9163 |
| 0.4058        | 7.0   | 5908  | 0.3682          | 0.9163 |
| 0.4057        | 8.0   | 6752  | 0.3767          | 0.9163 |
| 0.3807        | 9.0   | 7596  | 0.3519          | 0.9163 |
| 0.394         | 10.0  | 8440  | 0.3603          | 0.9163 |
| 0.39          | 11.0  | 9284  | 0.3630          | 0.9163 |
| 0.3945        | 12.0  | 10128 | 0.3846          | 0.9163 |
| 0.3948        | 13.0  | 10972 | 0.3711          | 0.9163 |
| 0.3981        | 14.0  | 11816 | 0.3516          | 0.9163 |
| 0.4144        | 15.0  | 12660 | 0.3526          | 0.9163 |
| 0.3999        | 16.0  | 13504 | 0.3560          | 0.9163 |
| 0.376         | 17.0  | 14348 | 0.3671          | 0.9163 |
| 0.412         | 18.0  | 15192 | 0.3630          | 0.9163 |
| 0.389         | 19.0  | 16036 | 0.3669          | 0.9136 |
| 0.374         | 20.0  | 16880 | 0.3713          | 0.9129 |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3