---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper-Small-TF-TIMIT
  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-Small-TF-TIMIT

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: 0.7104
- Wer: 98.0856

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3408        | 3.45  | 500  | 0.3994          | 83.6838 |
| 0.2057        | 6.9   | 1000 | 0.4079          | 92.3470 |
| 0.0616        | 10.34 | 1500 | 0.5076          | 94.2053 |
| 0.023         | 13.79 | 2000 | 0.5998          | 95.3184 |
| 0.0043        | 17.24 | 2500 | 0.6825          | 97.1284 |
| 0.0023        | 20.69 | 3000 | 0.7104          | 98.0856 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2