File size: 4,116 Bytes
fe748eb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
- precision
- f1
model-index:
- name: wav2vec2-large
  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

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the galsenai/waxal_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3413
- Accuracy: 0.9443
- Precision: 0.9780
- F1: 0.9604

## 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: 3e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 0
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 32.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|
| 4.6314        | 1.01  | 500   | 4.9165          | 0.0205   | 0.0028    | 0.0049 |
| 3.7739        | 2.02  | 1000  | 4.4491          | 0.0356   | 0.0750    | 0.0252 |
| 2.5035        | 3.04  | 1500  | 4.1429          | 0.1129   | 0.2672    | 0.1114 |
| 1.5633        | 4.05  | 2000  | 3.1973          | 0.3676   | 0.6598    | 0.3830 |
| 1.0538        | 5.06  | 2500  | 2.5479          | 0.5889   | 0.8417    | 0.6557 |
| 0.7422        | 6.07  | 3000  | 1.4494          | 0.7825   | 0.8921    | 0.8194 |
| 0.5762        | 7.08  | 3500  | 1.3168          | 0.7726   | 0.9277    | 0.8267 |
| 0.46          | 8.1   | 4000  | 0.8783          | 0.8564   | 0.9532    | 0.8982 |
| 0.4007        | 9.11  | 4500  | 0.7524          | 0.8738   | 0.9637    | 0.9137 |
| 0.3374        | 10.12 | 5000  | 0.6386          | 0.8852   | 0.9678    | 0.9221 |
| 0.3108        | 11.13 | 5500  | 0.5049          | 0.9106   | 0.9681    | 0.9373 |
| 0.2735        | 12.15 | 6000  | 0.6097          | 0.8905   | 0.9624    | 0.9226 |
| 0.2716        | 13.16 | 6500  | 0.4543          | 0.9000   | 0.9569    | 0.9206 |
| 0.2484        | 14.17 | 7000  | 0.3965          | 0.9272   | 0.9742    | 0.9489 |
| 0.228         | 15.18 | 7500  | 0.6807          | 0.8856   | 0.9777    | 0.9257 |
| 0.2307        | 16.19 | 8000  | 0.5219          | 0.9174   | 0.9802    | 0.9464 |
| 0.2169        | 17.21 | 8500  | 0.4630          | 0.9121   | 0.9677    | 0.9338 |
| 0.1997        | 18.22 | 9000  | 0.5152          | 0.9128   | 0.9740    | 0.9398 |
| 0.1921        | 19.23 | 9500  | 0.5105          | 0.9144   | 0.9867    | 0.9476 |
| 0.1825        | 20.24 | 10000 | 0.6302          | 0.9053   | 0.9832    | 0.9407 |
| 0.1786        | 21.25 | 10500 | 0.4602          | 0.9272   | 0.9813    | 0.9524 |
| 0.1671        | 22.27 | 11000 | 0.5443          | 0.9147   | 0.9794    | 0.9444 |
| 0.1623        | 23.28 | 11500 | 0.3413          | 0.9443   | 0.9780    | 0.9604 |
| 0.1595        | 24.29 | 12000 | 0.4478          | 0.9288   | 0.9813    | 0.9531 |
| 0.151         | 25.3  | 12500 | 0.4178          | 0.9360   | 0.9818    | 0.9571 |
| 0.1472        | 26.32 | 13000 | 0.4154          | 0.9356   | 0.9833    | 0.9578 |
| 0.1473        | 27.33 | 13500 | 0.4549          | 0.9318   | 0.9837    | 0.9561 |
| 0.131         | 28.34 | 14000 | 0.3574          | 0.9424   | 0.9845    | 0.9621 |
| 0.134         | 29.35 | 14500 | 0.4475          | 0.9333   | 0.9840    | 0.9568 |
| 0.1282        | 30.36 | 15000 | 0.4012          | 0.9382   | 0.9837    | 0.9591 |
| 0.1307        | 31.38 | 15500 | 0.3552          | 0.9428   | 0.9847    | 0.9624 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2