---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Base EN
  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. -->

# Whisper Base EN

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the ADLINK dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Wer: 33.6364

## 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: 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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4926        | 25.0  | 100  | 0.1674          | 57.5758 |
| 0.0002        | 50.0  | 200  | 0.0001          | 3.9394  |
| 0.0001        | 75.0  | 300  | 0.0001          | 5.1515  |
| 0.0001        | 100.0 | 400  | 0.0001          | 10.3030 |
| 0.0001        | 125.0 | 500  | 0.0001          | 11.5152 |
| 0.0           | 150.0 | 600  | 0.0000          | 28.4848 |
| 0.0           | 175.0 | 700  | 0.0000          | 30.0    |
| 0.0           | 200.0 | 800  | 0.0000          | 29.0909 |
| 0.0           | 225.0 | 900  | 0.0000          | 33.6364 |
| 0.0           | 250.0 | 1000 | 0.0000          | 33.6364 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.19.1
- Tokenizers 0.19.1