File size: 1,807 Bytes
a59b837
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: mit
base_model: xlm-roberta-base
tags:
- generated_from_trainer
model-index:
- name: QA_SYNTH_DATA_WITH_UNANSWERABLE_05_SEPT
  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. -->

# QA_SYNTH_DATA_WITH_UNANSWERABLE_05_SEPT

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0053

## 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: 2
- eval_batch_size: 2
- 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 |
|:-------------:|:-----:|:------:|:---------------:|
| 0.0478        | 1.0   | 16275  | 0.0446          |
| 0.0825        | 2.0   | 32550  | 0.0349          |
| 0.0674        | 3.0   | 48825  | 0.0366          |
| 0.0088        | 4.0   | 65100  | 0.0301          |
| 0.0102        | 5.0   | 81375  | 0.0110          |
| 0.0036        | 6.0   | 97650  | 0.0040          |
| 0.0           | 7.0   | 113925 | 0.0055          |
| 0.0           | 8.0   | 130200 | 0.0056          |
| 0.0           | 9.0   | 146475 | 0.0052          |
| 0.0           | 10.0  | 162750 | 0.0053          |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3