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

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

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0317
- Wer: 16.4220

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0595        | 0.4   | 1000 | 0.0904          | 42.5230 |
| 0.0339        | 0.79  | 2000 | 0.0593          | 30.1319 |
| 0.0171        | 1.19  | 3000 | 0.0441          | 23.5133 |
| 0.0133        | 1.58  | 4000 | 0.0363          | 19.1092 |
| 0.0096        | 1.98  | 5000 | 0.0317          | 16.4220 |


### Framework versions

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