---
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_increased_learning
  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. -->

# msc_imasc_openslr_festfox_Whisper_Medium_2_increased_learning

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: 0.0293
- Wer: 13.7099

## 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: 3e-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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0595        | 0.4   | 1000 | 0.1031          | 45.0858 |
| 0.0357        | 0.79  | 2000 | 0.0648          | 31.0774 |
| 0.0189        | 1.19  | 3000 | 0.0454          | 23.8119 |
| 0.0137        | 1.58  | 4000 | 0.0356          | 18.2632 |
| 0.0086        | 1.98  | 5000 | 0.0308          | 15.7751 |
| 0.0031        | 2.37  | 6000 | 0.0293          | 13.7099 |


### Framework versions

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