---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: openai/whisper-medium
  results: []
---

<!-- 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. -->

# openai/whisper-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the pphuc25/EngMed dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1345
- Wer: 46.9544

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 1.1104        | 1.0   | 2506  | 1.7078          | 53.9259 |
| 0.5898        | 2.0   | 5012  | 1.7177          | 48.6772 |
| 0.2178        | 3.0   | 7518  | 1.9259          | 49.4297 |
| 0.0721        | 4.0   | 10024 | 2.0441          | 47.6360 |
| 0.0098        | 5.0   | 12530 | 2.1345          | 46.9544 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1