File size: 1,742 Bytes
b3d04e9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: disitlbert_finetunedmodel
  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. -->

# disitlbert_finetunedmodel

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4268

## 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: 2e-05
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.5666        | 1.0   | 520  | 1.2041          |
| 1.2334        | 2.0   | 1040 | 1.1728          |
| 1.1474        | 3.0   | 1560 | 1.1650          |
| 1.0639        | 4.0   | 2080 | 1.2005          |
| 1.0005        | 5.0   | 2600 | 1.1893          |
| 0.9307        | 6.0   | 3120 | 1.2277          |
| 0.872         | 7.0   | 3640 | 1.3071          |
| 0.8073        | 8.0   | 4160 | 1.2973          |
| 0.7666        | 9.0   | 4680 | 1.3650          |
| 0.7281        | 10.0  | 5200 | 1.4268          |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.13.0
- Tokenizers 0.13.3