README.md

---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper-Anuj-small-Telugu-final
  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-Anuj-small-Telugu-final

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1426
- Wer: 34.9876
- Cer: 11.4531

## 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: 6
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1800

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     | Cer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
| 0.0642        | 3.9474  | 600  | 0.1178          | 43.0273 | 8.8399  |
| 0.0046        | 7.8947  | 1200 | 0.1248          | 35.9801 | 8.3327  |
| 0.0003        | 11.8421 | 1800 | 0.1426          | 34.9876 | 11.4531 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1