---
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-combined-5hrs-62
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: bigcgen
      type: bigcgen
    metrics:
    - name: Wer
      type: wer
      value: 0.5565156468939748
---

<!-- 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-combined-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: 0.7209
- Wer: 0.5565

## 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.0959        | 0.6079 | 200  | 0.9655          | 0.6610 |
| 0.6562        | 1.2158 | 400  | 0.8052          | 0.5699 |
| 0.6063        | 1.8237 | 600  | 0.7209          | 0.5565 |
| 0.402         | 2.4316 | 800  | 0.7347          | 0.5566 |
| 0.3066        | 3.0395 | 1000 | 0.7320          | 0.5467 |
| 0.2262        | 3.6474 | 1200 | 0.7329          | 0.5896 |
| 0.117         | 4.2553 | 1400 | 0.7819          | 0.5211 |


### Framework versions

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