---
language:
- en
tags:
- hf-asr-leaderboard
- generated_from_trainer
base_model: openai/whisper-medium.en
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.en](https://huggingface.co/openai/whisper-medium.en) on the ADLINK dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0017
- Wer: 1.3384

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 2.7899        | 4.1667  | 100  | 2.3530          | 21.4149 |
| 0.8377        | 8.3333  | 200  | 0.7500          | 4.2065  |
| 0.0599        | 12.5    | 300  | 0.0394          | 1.9120  |
| 0.0163        | 16.6667 | 400  | 0.0151          | 2.1033  |
| 0.0068        | 20.8333 | 500  | 0.0023          | 1.1472  |
| 0.0031        | 25.0    | 600  | 0.0018          | 1.3384  |
| 0.0027        | 29.1667 | 700  | 0.0023          | 1.3384  |
| 0.0018        | 33.3333 | 800  | 0.0020          | 1.3384  |
| 0.003         | 37.5    | 900  | 0.0017          | 1.3384  |
| 0.0009        | 41.6667 | 1000 | 0.0017          | 1.3384  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.19.2
- Tokenizers 0.19.1