---
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-male-5hrs-model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: bigcgen
      type: bigcgen
    metrics:
    - name: Wer
      type: wer
      value: 0.5054099543159414
---

<!-- 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-male-5hrs-model

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: 0.6817
- Wer: 0.5054

## 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: 1.75e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.6678        | 0.6211 | 200  | 0.8233          | 0.6018 |
| 2.3045        | 1.2422 | 400  | 0.7233          | 0.6420 |
| 2.7509        | 1.8634 | 600  | 0.6881          | 0.5239 |
| 1.7043        | 2.4845 | 800  | 0.6817          | 0.5054 |
| 0.8068        | 3.1056 | 1000 | 0.7271          | 0.4915 |
| 0.9957        | 3.7267 | 1200 | 0.7331          | 0.4893 |
| 0.3976        | 4.3478 | 1400 | 0.7714          | 0.4943 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0