---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bigcgen
metrics:
- wer
model-index:
- name: whisper-medium-bigcgen-female-5hrs-62
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: bigcgen
      type: bigcgen
    metrics:
    - name: Wer
      type: wer
      value: 0.548921679909194
---

<!-- 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-medium-bigcgen-female-5hrs-62

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the bigcgen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7278
- Wer: 0.5489

## 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: 2
- eval_batch_size: 2
- seed: 62
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.0539        | 0.5984 | 200  | 1.0387          | 0.6708 |
| 0.7105        | 1.1945 | 400  | 0.8432          | 0.5764 |
| 0.6344        | 1.7928 | 600  | 0.7586          | 0.5600 |
| 0.5221        | 2.3889 | 800  | 0.7457          | 0.5623 |
| 0.4151        | 2.9873 | 1000 | 0.7278          | 0.5489 |
| 0.219         | 3.5834 | 1200 | 0.7980          | 0.5287 |
| 0.1226        | 4.1795 | 1400 | 0.8193          | 0.5362 |
| 0.1245        | 4.7779 | 1600 | 0.8030          | 0.4976 |
| 0.0529        | 5.3740 | 1800 | 0.8765          | 0.4963 |


### Framework versions

- Transformers 4.53.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.0