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---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.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-medium.en](https://huggingface.co/openai/whisper-medium.en) on the ADLINK dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Wer: 448.7879
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1004 | 25.0 | 100 | 1.0484 | 2.1212 |
| 0.3934 | 50.0 | 200 | 0.4056 | 45.7576 |
| 0.0206 | 75.0 | 300 | 0.0131 | 63.3333 |
| 0.0012 | 100.0 | 400 | 0.0012 | 280.0 |
| 0.0006 | 125.0 | 500 | 0.0006 | 319.6970 |
| 0.0004 | 150.0 | 600 | 0.0004 | 381.5152 |
| 0.0003 | 175.0 | 700 | 0.0003 | 380.0 |
| 0.0003 | 200.0 | 800 | 0.0003 | 497.8788 |
| 0.0003 | 225.0 | 900 | 0.0003 | 462.7273 |
| 0.0003 | 250.0 | 1000 | 0.0003 | 448.7879 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.19.1
- Tokenizers 0.19.1
|