File size: 2,610 Bytes
1295255
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
82
83
84
85
---
language:
- en
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: nlp-mini-prj
  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. -->

# nlp-mini-prj

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: 0.0000

## 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
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.0841        | 3.76  | 500   | 0.0005          |
| 0.0015        | 7.52  | 1000  | 0.0002          |
| 0.0011        | 11.28 | 1500  | 0.0001          |
| 0.0042        | 15.04 | 2000  | 0.0001          |
| 0.0008        | 18.8  | 2500  | 0.0001          |
| 0.0004        | 22.56 | 3000  | 0.0001          |
| 0.0001        | 26.32 | 3500  | 0.0000          |
| 0.0001        | 30.08 | 4000  | 0.0000          |
| 0.0001        | 33.83 | 4500  | 0.0000          |
| 0.0001        | 37.59 | 5000  | 0.0000          |
| 0.0           | 41.35 | 5500  | 0.0000          |
| 0.0           | 45.11 | 6000  | 0.0000          |
| 0.0           | 48.87 | 6500  | 0.0000          |
| 0.0           | 52.63 | 7000  | 0.0000          |
| 0.0           | 56.39 | 7500  | 0.0000          |
| 0.0           | 60.15 | 8000  | 0.0000          |
| 0.0           | 63.91 | 8500  | 0.0000          |
| 0.0           | 67.67 | 9000  | 0.0000          |
| 0.0           | 71.43 | 9500  | 0.0000          |
| 0.0           | 75.19 | 10000 | 0.0000          |
| 0.0           | 78.95 | 10500 | 0.0000          |
| 0.0           | 82.71 | 11000 | 0.0000          |
| 0.0           | 86.47 | 11500 | 0.0000          |
| 0.0           | 90.23 | 12000 | 0.0000          |
| 0.0           | 93.98 | 12500 | 0.0000          |
| 0.0           | 97.74 | 13000 | 0.0000          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0