File size: 1,756 Bytes
a5e4bd1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a0c37ab
a5e4bd1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a0c37ab
a5e4bd1
 
 
 
 
a0c37ab
a5e4bd1
 
 
 
 
a0c37ab
 
 
 
 
 
 
 
 
 
a5e4bd1
 
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: distilroberta-base
tags:
- generated_from_trainer
model-index:
- name: my_awesome_distilberta_lm
  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. -->

# my_awesome_distilberta_lm

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: 4.4099

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 282  | 5.3874          |
| 5.4769        | 2.0   | 564  | 5.2643          |
| 5.4769        | 3.0   | 846  | 4.9845          |
| 5.075         | 4.0   | 1128 | 4.9163          |
| 5.075         | 5.0   | 1410 | 4.8219          |
| 4.799         | 6.0   | 1692 | 4.6897          |
| 4.799         | 7.0   | 1974 | 4.5800          |
| 4.5388        | 8.0   | 2256 | 4.5920          |
| 4.3687        | 9.0   | 2538 | 4.5769          |
| 4.3687        | 10.0  | 2820 | 4.4824          |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1
- Datasets 2.14.6
- Tokenizers 0.13.3