File size: 3,834 Bytes
0916bb0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: distilbert-finetuned-lr1e-05-epochs50
  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. -->

# distilbert-finetuned-lr1e-05-epochs50

This model is a fine-tuned version of [distilbert-base-cased-distilled-squad](https://huggingface.co/distilbert-base-cased-distilled-squad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.5477

## 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: 1e-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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 10   | 4.0110          |
| No log        | 2.0   | 20   | 3.3394          |
| No log        | 3.0   | 30   | 3.1992          |
| No log        | 4.0   | 40   | 2.9902          |
| No log        | 5.0   | 50   | 2.9628          |
| No log        | 6.0   | 60   | 2.9346          |
| No log        | 7.0   | 70   | 2.9844          |
| No log        | 8.0   | 80   | 2.9660          |
| No log        | 9.0   | 90   | 2.9239          |
| No log        | 10.0  | 100  | 3.0764          |
| No log        | 11.0  | 110  | 3.1964          |
| No log        | 12.0  | 120  | 3.2409          |
| No log        | 13.0  | 130  | 3.3191          |
| No log        | 14.0  | 140  | 3.3747          |
| No log        | 15.0  | 150  | 3.5559          |
| No log        | 16.0  | 160  | 3.6678          |
| No log        | 17.0  | 170  | 3.6692          |
| No log        | 18.0  | 180  | 3.7116          |
| No log        | 19.0  | 190  | 3.6768          |
| No log        | 20.0  | 200  | 3.7929          |
| No log        | 21.0  | 210  | 3.8766          |
| No log        | 22.0  | 220  | 3.8967          |
| No log        | 23.0  | 230  | 3.8982          |
| No log        | 24.0  | 240  | 3.9140          |
| No log        | 25.0  | 250  | 3.9563          |
| No log        | 26.0  | 260  | 3.9702          |
| No log        | 27.0  | 270  | 3.9615          |
| No log        | 28.0  | 280  | 4.0481          |
| No log        | 29.0  | 290  | 4.1172          |
| No log        | 30.0  | 300  | 4.2297          |
| No log        | 31.0  | 310  | 4.3585          |
| No log        | 32.0  | 320  | 4.3186          |
| No log        | 33.0  | 330  | 4.2844          |
| No log        | 34.0  | 340  | 4.2662          |
| No log        | 35.0  | 350  | 4.3037          |
| No log        | 36.0  | 360  | 4.4106          |
| No log        | 37.0  | 370  | 4.4208          |
| No log        | 38.0  | 380  | 4.3877          |
| No log        | 39.0  | 390  | 4.4133          |
| No log        | 40.0  | 400  | 4.4798          |
| No log        | 41.0  | 410  | 4.4925          |
| No log        | 42.0  | 420  | 4.4595          |
| No log        | 43.0  | 430  | 4.4402          |
| No log        | 44.0  | 440  | 4.4379          |
| No log        | 45.0  | 450  | 4.4711          |
| No log        | 46.0  | 460  | 4.4953          |
| No log        | 47.0  | 470  | 4.5282          |
| No log        | 48.0  | 480  | 4.5400          |
| No log        | 49.0  | 490  | 4.5472          |
| 0.4112        | 50.0  | 500  | 4.5477          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3