---
language:
- en
license: apache-2.0
base_model: openai/whisper-base.en
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-base.en](https://huggingface.co/openai/whisper-base.en) on the ADLINK dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Wer: 1.2422

## 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     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.5447        | 33.33  | 100  | 1.2099          | 11.4907 |
| 0.4211        | 66.67  | 200  | 0.3868          | 1.5528  |
| 0.0987        | 100.0  | 300  | 0.0761          | 1.8634  |
| 0.006         | 133.33 | 400  | 0.0040          | 1.2422  |
| 0.0011        | 166.67 | 500  | 0.0010          | 1.2422  |
| 0.0006        | 200.0  | 600  | 0.0006          | 1.2422  |
| 0.0004        | 233.33 | 700  | 0.0004          | 1.2422  |
| 0.0003        | 266.67 | 800  | 0.0003          | 1.2422  |
| 0.0003        | 300.0  | 900  | 0.0003          | 1.2422  |
| 0.0003        | 333.33 | 1000 | 0.0003          | 1.2422  |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1