---
language:
- ta
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper tiny Ta example - Bharat Ramanathan
  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 example - Bharat Ramanathan

This model is a fine-tuned version of [parambharat/whisper-tiny-ta](https://huggingface.co/parambharat/whisper-tiny-ta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4016
- Wer: 36.5217

## 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: 25
- training_steps: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.304         | 12.01 | 25   | 0.3614          | 31.7391 |
| 0.1826        | 24.02 | 50   | 0.3851          | 35.2174 |
| 0.1346        | 37.01 | 75   | 0.3999          | 37.8261 |
| 0.1096        | 49.02 | 100  | 0.4016          | 36.5217 |


### Framework versions

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