---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: imasc_openslr_festfox
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# imasc_openslr_festfox

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: 0.0572
- Wer: 28.1413

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0795        | 0.41  | 1000 | 0.1409          | 60.0398 |
| 0.0494        | 0.82  | 2000 | 0.0887          | 43.3441 |
| 0.0272        | 1.23  | 3000 | 0.0731          | 37.3227 |
| 0.0187        | 1.64  | 4000 | 0.0653          | 34.3867 |
| 0.0089        | 2.06  | 5000 | 0.0583          | 29.8333 |
| 0.0093        | 2.47  | 6000 | 0.0572          | 28.1413 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1