---
language:
- ka
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
model-index:
- name: whisper-small-tamil
  results: 
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs
        config: ta_in
        split: test
        type: google/fleurs
      metrics:
        - name: Wer
          type: wer
          value: 23.1257
---

<!-- 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-small-tamil

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset for Kannada.
It achieves the following results on the evaluation set:
- Loss:  0.2507
- Wer: 23.1257
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0792        | 2.27  | 500  | 0.2674          | 24.7048 |
| 0.0067        | 12.19 | 1000 | 0.1930          | 23.7758 |
| 0.0011        | 18.29 | 1500 | 0.2161          | 23.3225 |
| 0.0002        | 24.39 | 2000 | 0.2294          | 23.1332 |
| 0.0001        | 30.48 | 2500 | 0.2406          | 23.1652 |
| 0.0001        | 36.58 | 3000 | 0.2461          | 23.1531 |
| 0.0001        | 42.68 | 3500 | 0.2493          | 23.1108 |
| 0.0001        | 48.78 | 4000 | 0.2507          | 23.1257 |

### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2