File size: 2,061 Bytes
abfda8f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: wav2vec-fine_tuned-speech_command2
  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. -->

# wav2vec-fine_tuned-speech_command2

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co./facebook/wav2vec2-base) on the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1040
- Accuracy: 0.9735

## 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: 256
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3874        | 1.0   | 50   | 0.9633          | 0.9229   |
| 0.5144        | 2.0   | 100  | 0.4398          | 0.9138   |
| 0.3538        | 3.0   | 150  | 0.1688          | 0.9651   |
| 0.2956        | 4.0   | 200  | 0.1622          | 0.9623   |
| 0.2662        | 5.0   | 250  | 0.1425          | 0.9665   |
| 0.2122        | 6.0   | 300  | 0.1301          | 0.9682   |
| 0.1948        | 7.0   | 350  | 0.1232          | 0.9693   |
| 0.1837        | 8.0   | 400  | 0.1116          | 0.9734   |
| 0.1631        | 9.0   | 450  | 0.1041          | 0.9734   |
| 0.1441        | 10.0  | 500  | 0.1040          | 0.9735   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3