---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: msc_imasc_openslr_festfox_Whisper_Medium_2
  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_2

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: 0.0424
- Wer: 18.1637

## 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: 5e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0482        | 0.79  | 1000 | 0.0801          | 40.4827 |
| 0.0238        | 1.58  | 2000 | 0.0514          | 27.4944 |
| 0.0105        | 2.37  | 3000 | 0.0447          | 22.8415 |
| 0.0044        | 3.16  | 4000 | 0.0403          | 19.3580 |
| 0.0037        | 3.95  | 5000 | 0.0408          | 19.3083 |
| 0.0016        | 4.74  | 6000 | 0.0424          | 18.1637 |


### Framework versions

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