File size: 1,406 Bytes
e71ff72
 
 
 
ade1746
4771df5
e71ff72
4771df5
 
e71ff72
 
 
 
 
4771df5
e71ff72
4771df5
ade1746
3410369
 
 
 
 
 
 
e71ff72
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4771df5
e71ff72
 
 
 
 
 
 
 
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
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- tamil_asr_corpus
model-index:
- name: whisper-tiny-ta
  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. -->

# whisper-tiny-ta

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the tamil_asr_corpus dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3112
- eval_wer: 30.1832
- eval_runtime: 3154.5468
- eval_samples_per_second: 3.743
- eval_steps_per_second: 0.234
- epoch: 0.4
- step: 9000

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2