File size: 2,122 Bytes
81e4739
f71684d
5be5cb1
f71684d
 
5be5cb1
 
38f3515
 
 
81e4739
 
38f3515
 
81e4739
38f3515
81e4739
f71684d
38f3515
f71684d
 
81e4739
38f3515
81e4739
38f3515
81e4739
38f3515
81e4739
38f3515
81e4739
38f3515
81e4739
38f3515
81e4739
38f3515
81e4739
38f3515
81e4739
38f3515
 
f71684d
38f3515
 
 
f71684d
38f3515
 
 
 
 
81e4739
38f3515
81e4739
38f3515
 
f71684d
 
 
 
 
 
 
 
 
81e4739
 
38f3515
81e4739
38f3515
 
 
 
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
---
base_model: jmaczan/wav2vec2-large-xls-r-300m-dysarthria-big-dataset
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-dysarthria-big-dataset
  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. -->

# wav2vec2-large-xls-r-300m-dysarthria-big-dataset

This model is a fine-tuned version of [jmaczan/wav2vec2-large-xls-r-300m-dysarthria-big-dataset](https://huggingface.co/jmaczan/wav2vec2-large-xls-r-300m-dysarthria-big-dataset) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0864
- Wer: 0.182

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer   |
|:-------------:|:-----:|:----:|:---------------:|:-----:|
| 1.419         | 3.2   | 200  | 0.7599          | 0.668 |
| 0.7759        | 6.4   | 400  | 0.4966          | 0.618 |
| 0.5808        | 9.6   | 600  | 0.3352          | 0.508 |
| 0.3652        | 12.8  | 800  | 0.2214          | 0.386 |
| 0.2347        | 16.0  | 1000 | 0.1566          | 0.246 |
| 0.1738        | 19.2  | 1200 | 0.1340          | 0.23  |
| 0.1076        | 22.4  | 1400 | 0.1244          | 0.242 |
| 0.077         | 25.6  | 1600 | 0.0948          | 0.184 |
| 0.0566        | 28.8  | 1800 | 0.0864          | 0.182 |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1