---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: whisper-tiny-tamil
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Speech Commands
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7142857142857143
---

<!-- 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-tamil

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the Speech Commands dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6296
- Accuracy: 0.7143

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9817        | 1.0   | 55   | 1.0006          | 0.5714   |
| 0.894         | 2.0   | 110  | 0.8903          | 0.5714   |
| 0.7656        | 3.0   | 165  | 0.8475          | 0.7143   |
| 0.5697        | 4.0   | 220  | 0.7843          | 0.6429   |
| 0.8338        | 5.0   | 275  | 0.7055          | 0.6429   |
| 0.6986        | 6.0   | 330  | 0.7369          | 0.7143   |
| 0.5099        | 7.0   | 385  | 0.6787          | 0.7143   |
| 0.5774        | 8.0   | 440  | 0.6369          | 0.7143   |
| 0.7313        | 9.0   | 495  | 0.6106          | 0.7857   |
| 0.5775        | 10.0  | 550  | 0.6296          | 0.7143   |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.2.2
- Datasets 3.2.0
- Tokenizers 0.21.0