File size: 1,853 Bytes
4589f91
 
 
 
 
90f2f66
 
4589f91
 
 
 
 
 
 
 
 
 
 
90f2f66
 
 
4589f91
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
90f2f66
4589f91
 
 
90f2f66
 
 
 
 
 
 
 
 
 
 
4589f91
 
 
 
 
 
 
 
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
---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_multiple_choice
  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. -->

# roberta_multiple_choice

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2868
- Accuracy: 0.58

## 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-06
- 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: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4619        | 1.0   | 3207  | 1.2367          | 0.51     |
| 1.3209        | 2.0   | 6414  | 1.1911          | 0.525    |
| 1.2195        | 3.0   | 9621  | 1.1396          | 0.525    |
| 1.1211        | 4.0   | 12828 | 1.1321          | 0.53     |
| 1.0221        | 5.0   | 16035 | 1.2210          | 0.535    |
| 0.9262        | 6.0   | 19242 | 1.2008          | 0.555    |
| 0.8418        | 7.0   | 22449 | 1.2451          | 0.555    |
| 0.7691        | 8.0   | 25656 | 1.2793          | 0.555    |
| 0.6981        | 9.0   | 28863 | 1.2868          | 0.58     |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3