File size: 4,899 Bytes
7afd67f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
064a1bb
 
7afd67f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
064a1bb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7afd67f
 
 
 
 
 
 
 
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
107
108
109
110
111
112
113
114
115
116
117
118
---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
model-index:
- name: camembert_question_answering_tools_fr
  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. -->

# camembert_question_answering_tools_fr

This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8470
- Learning Rate: 0.0

## 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: 0.0001
- train_batch_size: 24
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 1.0   | 7    | 4.1208          | 0.0001 |
| No log        | 2.0   | 14   | 3.2825          | 0.0001 |
| No log        | 3.0   | 21   | 3.0182          | 0.0001 |
| No log        | 4.0   | 28   | 2.8863          | 0.0001 |
| No log        | 5.0   | 35   | 2.8072          | 0.0001 |
| No log        | 6.0   | 42   | 2.7408          | 9e-05  |
| No log        | 7.0   | 49   | 2.6830          | 0.0001 |
| No log        | 8.0   | 56   | 2.6311          | 0.0001 |
| No log        | 9.0   | 63   | 2.5832          | 0.0001 |
| No log        | 10.0  | 70   | 2.5409          | 0.0001 |
| No log        | 11.0  | 77   | 2.5002          | 0.0001 |
| No log        | 12.0  | 84   | 2.4644          | 8e-05  |
| No log        | 13.0  | 91   | 2.6593          | 0.0001 |
| No log        | 14.0  | 98   | 3.1933          | 0.0001 |
| No log        | 15.0  | 105  | 2.8660          | 0.0001 |
| No log        | 16.0  | 112  | 2.8877          | 0.0001 |
| No log        | 17.0  | 119  | 2.8835          | 0.0001 |
| No log        | 18.0  | 126  | 3.1413          | 7e-05  |
| No log        | 19.0  | 133  | 2.3645          | 0.0001 |
| No log        | 20.0  | 140  | 2.6474          | 0.0001 |
| No log        | 21.0  | 147  | 2.6844          | 0.0001 |
| No log        | 22.0  | 154  | 2.6115          | 0.0001 |
| No log        | 23.0  | 161  | 2.6331          | 0.0001 |
| No log        | 24.0  | 168  | 2.6264          | 6e-05  |
| No log        | 25.0  | 175  | 2.8091          | 0.0001 |
| No log        | 26.0  | 182  | 3.0149          | 0.0001 |
| No log        | 27.0  | 189  | 3.1302          | 0.0001 |
| No log        | 28.0  | 196  | 3.3069          | 0.0001 |
| No log        | 29.0  | 203  | 2.9019          | 0.0001 |
| No log        | 30.0  | 210  | 2.9813          | 5e-05  |
| No log        | 31.0  | 217  | 3.0455          | 0.0000 |
| No log        | 32.0  | 224  | 2.5279          | 0.0000 |
| No log        | 33.0  | 231  | 2.3590          | 0.0000 |
| No log        | 34.0  | 238  | 2.1238          | 0.0000 |
| No log        | 35.0  | 245  | 2.0876          | 0.0000 |
| No log        | 36.0  | 252  | 2.2768          | 4e-05  |
| No log        | 37.0  | 259  | 2.1171          | 0.0000 |
| No log        | 38.0  | 266  | 2.0958          | 0.0000 |
| No log        | 39.0  | 273  | 2.1616          | 0.0000 |
| No log        | 40.0  | 280  | 2.0285          | 0.0000 |
| No log        | 41.0  | 287  | 1.8582          | 0.0000 |
| No log        | 42.0  | 294  | 1.7696          | 3e-05  |
| No log        | 43.0  | 301  | 1.6826          | 0.0000 |
| No log        | 44.0  | 308  | 2.1097          | 0.0000 |
| No log        | 45.0  | 315  | 1.8101          | 0.0000 |
| No log        | 46.0  | 322  | 1.8781          | 0.0000 |
| No log        | 47.0  | 329  | 1.6785          | 0.0000 |
| No log        | 48.0  | 336  | 1.7334          | 2e-05  |
| No log        | 49.0  | 343  | 1.7917          | 0.0000 |
| No log        | 50.0  | 350  | 1.6310          | 0.0000 |
| No log        | 51.0  | 357  | 1.5047          | 0.0000 |
| No log        | 52.0  | 364  | 1.6845          | 0.0000 |
| No log        | 53.0  | 371  | 1.6887          | 0.0000 |
| No log        | 54.0  | 378  | 1.6869          | 1e-05  |
| No log        | 55.0  | 385  | 1.6888          | 0.0000 |
| No log        | 56.0  | 392  | 1.7991          | 0.0000 |
| No log        | 57.0  | 399  | 1.8191          | 5e-06  |
| No log        | 58.0  | 406  | 1.8621          | 0.0000 |
| No log        | 59.0  | 413  | 1.8628          | 0.0000 |
| No log        | 60.0  | 420  | 1.8470          | 0.0    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1