File size: 1,992 Bytes
72d8b96
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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: facebook/hubert-base-ls960
tags:
- audio-classification
- hubert
- esc50
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-esc50-finetuned
  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. -->

# hubert-esc50-finetuned

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the ESC-50 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3860
- Accuracy: 0.3625

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.7931        | 1.0   | 200  | 3.7608          | 0.0275   |
| 3.6397        | 2.0   | 400  | 3.5743          | 0.065    |
| 3.3959        | 3.0   | 600  | 3.3550          | 0.0975   |
| 3.2348        | 4.0   | 800  | 3.1394          | 0.1375   |
| 2.9701        | 5.0   | 1000 | 2.9271          | 0.2175   |
| 2.9462        | 6.0   | 1200 | 2.7442          | 0.23     |
| 2.728         | 7.0   | 1400 | 2.6029          | 0.275    |
| 2.5537        | 8.0   | 1600 | 2.4791          | 0.3125   |
| 2.4586        | 9.0   | 1800 | 2.4028          | 0.35     |
| 2.3136        | 10.0  | 2000 | 2.3860          | 0.3625   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.1