File size: 2,644 Bytes
2691685
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c01d984
2691685
c01d984
 
2691685
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c01d984
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2691685
 
 
 
c01d984
2691685
 
 
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
---
license: apache-2.0
base_model: Harveenchadha/hindi_base_wav2vec2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hindi_beekeeping_wav2vec2-2
  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. -->

# hindi_beekeeping_wav2vec2-2

This model is a fine-tuned version of [Harveenchadha/hindi_base_wav2vec2](https://huggingface.co/Harveenchadha/hindi_base_wav2vec2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5244
- Wer: 0.3984

## 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: 10
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3815        | 4.55  | 25   | 1.0849          | 0.3984 |
| 0.1143        | 9.09  | 50   | 1.0752          | 0.3659 |
| 0.0827        | 13.64 | 75   | 1.4514          | 0.4390 |
| 0.0546        | 18.18 | 100  | 1.6510          | 0.4146 |
| 0.0506        | 22.73 | 125  | 1.5120          | 0.4593 |
| 0.0394        | 27.27 | 150  | 1.5948          | 0.4797 |
| 0.0356        | 31.82 | 175  | 1.4317          | 0.4228 |
| 0.0314        | 36.36 | 200  | 1.7475          | 0.4553 |
| 0.0278        | 40.91 | 225  | 1.6500          | 0.4634 |
| 0.0335        | 45.45 | 250  | 1.5310          | 0.4756 |
| 0.0213        | 50.0  | 275  | 1.4817          | 0.4593 |
| 0.0177        | 54.55 | 300  | 1.6921          | 0.4228 |
| 0.0115        | 59.09 | 325  | 1.6241          | 0.4106 |
| 0.0152        | 63.64 | 350  | 1.5167          | 0.4106 |
| 0.0109        | 68.18 | 375  | 1.7510          | 0.4553 |
| 0.011         | 72.73 | 400  | 1.6425          | 0.4146 |
| 0.0101        | 77.27 | 425  | 1.6253          | 0.4146 |
| 0.0091        | 81.82 | 450  | 1.6383          | 0.3984 |
| 0.008         | 86.36 | 475  | 1.5251          | 0.3984 |
| 0.0069        | 90.91 | 500  | 1.5244          | 0.3984 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1