File size: 1,817 Bytes
ba22e3d
 
 
 
dfc2e49
 
ba22e3d
 
 
 
 
 
 
 
 
 
dfc2e49
 
 
 
 
ba22e3d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
dfc2e49
 
 
 
 
 
 
 
 
 
 
ba22e3d
 
 
 
 
 
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
---
base_model: Alexander-Learn/bert-finetuned-squad
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-finetuned-squad-finetuned-DouRC_squad
  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. -->

# bert-finetuned-squad-finetuned-DouRC_squad

This model is a fine-tuned version of [Alexander-Learn/bert-finetuned-squad](https://huggingface.co/Alexander-Learn/bert-finetuned-squad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2794
- Exact Match: 0.725
- F1: 0.5962

## 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: 72
- eval_batch_size: 72
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1     |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------:|
| 1.1781        | 1.0   | 828  | 1.1097          | 0.72        | 0.6202 |
| 0.9177        | 2.0   | 1656 | 1.1056          | 0.715       | 0.5938 |
| 0.7366        | 3.0   | 2484 | 1.1415          | 0.715       | 0.5756 |
| 0.6056        | 4.0   | 3312 | 1.2132          | 0.71        | 0.5830 |
| 0.5191        | 5.0   | 4140 | 1.2794          | 0.725       | 0.5962 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1