---
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-baseline-42
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: bigcgen
      type: bigcgen
    metrics:
    - name: Wer
      type: wer
      value: 0.526129108536297
---

<!-- 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-baseline-42

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: 0.6970
- Wer: 0.5261

## 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: 42
- 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.0745        | 0.6102 | 200  | 0.9366          | 0.6486 |
| 0.6532        | 1.2197 | 400  | 0.7690          | 0.5467 |
| 0.6347        | 1.8299 | 600  | 0.7060          | 0.5129 |
| 0.4066        | 2.4394 | 800  | 0.6970          | 0.5261 |
| 0.2542        | 3.0488 | 1000 | 0.7140          | 0.5034 |
| 0.252         | 3.6590 | 1200 | 0.7221          | 0.4833 |
| 0.137         | 4.2685 | 1400 | 0.7573          | 0.4878 |
| 0.114         | 4.8787 | 1600 | 0.7934          | 0.4812 |


### Framework versions

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