File size: 4,479 Bytes
6b40356
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
---

language:
- ar
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium - Karthik Avinash
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: ar
      split: test
      args: 'config: ar, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 39.473684210526315
---


<!-- 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. -->

# Whisper Medium - Karthik Avinash

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4340
- Wer: 39.4737

## 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: 1e-05

- train_batch_size: 2

- eval_batch_size: 8

- seed: 42

- gradient_accumulation_steps: 16

- 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

- training_steps: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.0267        | 0.0166 | 20   | 1.1833          | 47.3684 |
| 0.7014        | 0.0333 | 40   | 0.9320          | 40.7895 |
| 0.5484        | 0.0499 | 60   | 0.6066          | 50.0    |
| 0.3202        | 0.0665 | 80   | 0.5057          | 56.5789 |
| 0.3791        | 0.0832 | 100  | 0.4702          | 47.3684 |
| 0.3701        | 0.0998 | 120  | 0.4606          | 46.0526 |
| 0.3584        | 0.1164 | 140  | 0.4618          | 47.3684 |
| 0.3459        | 0.1330 | 160  | 0.4809          | 51.3158 |
| 0.2758        | 0.1497 | 180  | 0.4729          | 52.6316 |
| 0.3636        | 0.1663 | 200  | 0.4597          | 48.6842 |
| 0.3649        | 0.1829 | 220  | 0.4475          | 43.4211 |
| 0.325         | 0.1996 | 240  | 0.4642          | 43.4211 |
| 0.3052        | 0.2162 | 260  | 0.4800          | 51.3158 |
| 0.1836        | 0.2328 | 280  | 0.4854          | 46.0526 |
| 0.2539        | 0.2495 | 300  | 0.4735          | 55.2632 |
| 0.3174        | 0.2661 | 320  | 0.4748          | 44.7368 |
| 0.3184        | 0.2827 | 340  | 0.4545          | 44.7368 |
| 0.2216        | 0.2994 | 360  | 0.4711          | 39.4737 |
| 0.2849        | 0.3160 | 380  | 0.4219          | 36.8421 |
| 0.2108        | 0.3326 | 400  | 0.4382          | 39.4737 |
| 0.2431        | 0.3493 | 420  | 0.4622          | 35.5263 |
| 0.2776        | 0.3659 | 440  | 0.4265          | 42.1053 |
| 0.3011        | 0.3825 | 460  | 0.4400          | 35.5263 |
| 0.2659        | 0.3991 | 480  | 0.5303          | 46.0526 |
| 0.3692        | 0.4158 | 500  | 0.4142          | 38.1579 |
| 0.3166        | 0.4324 | 520  | 0.4278          | 38.1579 |
| 0.2855        | 0.4490 | 540  | 0.4518          | 38.1579 |
| 0.2286        | 0.4657 | 560  | 0.4679          | 48.6842 |
| 0.2136        | 0.4823 | 580  | 0.4749          | 40.7895 |
| 0.2503        | 0.4989 | 600  | 0.4740          | 34.2105 |
| 0.1904        | 0.5156 | 620  | 0.4547          | 39.4737 |
| 0.376         | 0.5322 | 640  | 0.4272          | 40.7895 |
| 0.24          | 0.5488 | 660  | 0.4594          | 40.7895 |
| 0.2928        | 0.5655 | 680  | 0.4498          | 40.7895 |
| 0.2473        | 0.5821 | 700  | 0.4432          | 43.4211 |
| 0.5217        | 0.5987 | 720  | 0.4481          | 40.7895 |
| 0.1973        | 0.6154 | 740  | 0.4381          | 43.4211 |
| 0.272         | 0.6320 | 760  | 0.4407          | 39.4737 |
| 0.2364        | 0.6486 | 780  | 0.4345          | 40.7895 |
| 0.194         | 0.6652 | 800  | 0.4340          | 39.4737 |


### Framework versions

- Transformers 4.43.0.dev0
- Pytorch 2.4.0+cu124
- Datasets 2.20.0
- Tokenizers 0.19.1