---
language:
- ta
license: apache-2.0
base_model: openai/whisper-medium
tags:
- Tamil-ASR
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-tamil-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. -->

# whisper-medium-tamil-2

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1695
- Wer: 77.1245

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0174        | 1.14  | 100  | 1.0930          | 78.3945 |
| 0.0184        | 2.29  | 200  | 1.1317          | 76.6855 |
| 0.0103        | 3.43  | 300  | 1.1273          | 76.6541 |
| 0.0039        | 4.57  | 400  | 1.1638          | 76.7952 |
| 0.0014        | 5.71  | 500  | 1.1695          | 77.1245 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1