---
library_name: transformers
language:
- pmx
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- iitd-duk/paula
metrics:
- wer
model-index:
- name: Whisper-Small-paula
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Paula
      type: iitd-duk/paula
    metrics:
    - name: Wer
      type: wer
      value: 97.75910364145658
---

<!-- 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-paula

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Paula dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7488
- Wer: 97.7591

## 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: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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_steps: 100
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1           | 5.0   | 100  | 2.4980          | 131.0924 |
| 0.0249        | 10.0  | 200  | 2.5853          | 97.7591  |
| 0.0065        | 15.0  | 300  | 2.6842          | 98.0392  |
| 0.0026        | 20.0  | 400  | 2.7265          | 96.9188  |
| 0.0016        | 25.0  | 500  | 2.7488          | 97.7591  |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1