File size: 1,808 Bytes
e2d4e8c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: mit
base_model: microsoft/deberta-base-mnli
tags:
- generated_from_trainer
model-index:
- name: deberta_base_all
  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. -->

# deberta_base_all

This model is a fine-tuned version of [microsoft/deberta-base-mnli](https://huggingface.co/microsoft/deberta-base-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4071

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.5695        | 1.0   | 1949  | 0.4123          |
| 0.1587        | 2.0   | 3898  | 0.3700          |
| 0.0671        | 3.0   | 5847  | 0.3963          |
| 0.1556        | 4.0   | 7796  | 0.3373          |
| 0.103         | 5.0   | 9745  | 0.3485          |
| 0.1483        | 6.0   | 11694 | 0.4014          |
| 0.166         | 7.0   | 13643 | 0.3890          |
| 0.0515        | 8.0   | 15592 | 0.3875          |
| 0.0664        | 9.0   | 17541 | 0.4162          |
| 0.0321        | 10.0  | 19490 | 0.4071          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1