File size: 2,020 Bytes
bd5b0d6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mt5-base
  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. -->

# mt5-base

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0516
- Wer: 0.0392

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.4396        | 0.81  | 4000  | 0.3368          | 0.3043 |
| 0.4257        | 1.62  | 8000  | 0.1328          | 0.1205 |
| 0.2185        | 2.42  | 12000 | 0.0929          | 0.0879 |
| 0.1506        | 3.23  | 16000 | 0.0762          | 0.0708 |
| 0.1133        | 4.04  | 20000 | 0.0663          | 0.0587 |
| 0.092         | 4.85  | 24000 | 0.0620          | 0.0551 |
| 0.0739        | 5.66  | 28000 | 0.0583          | 0.0507 |
| 0.0649        | 6.46  | 32000 | 0.0572          | 0.0465 |
| 0.0564        | 7.27  | 36000 | 0.0545          | 0.0439 |
| 0.0494        | 8.08  | 40000 | 0.0533          | 0.0425 |
| 0.0433        | 8.89  | 44000 | 0.0522          | 0.0405 |
| 0.0396        | 9.7   | 48000 | 0.0516          | 0.0392 |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3