---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- bemgen
metrics:
- wer
model-index:
- name: whisper-medium-nyagen-combined-model
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: bemgen
      type: bemgen
    metrics:
    - name: Wer
      type: wer
      value: 0.19520264681555005
---

<!-- 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-nyagen-combined-model

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the bemgen dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2561
- Wer: 0.1952

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- 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    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.1602        | 0.5326 | 200  | 0.5182          | 0.3747 |
| 0.5456        | 1.0639 | 400  | 0.3445          | 0.2552 |
| 0.5516        | 1.5965 | 600  | 0.2903          | 0.2413 |
| 0.224         | 2.1278 | 800  | 0.2817          | 0.2384 |
| 0.2413        | 2.6605 | 1000 | 0.2561          | 0.1952 |
| 0.1036        | 3.1917 | 1200 | 0.2583          | 0.1904 |
| 0.1135        | 3.7244 | 1400 | 0.2637          | 0.2120 |
| 0.057         | 4.2557 | 1600 | 0.2731          | 0.2097 |


### Framework versions

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