metadata
language:
- en
tags:
- hf-asr-leaderboard
- generated_from_trainer
base_model: openai/whisper-medium.en
metrics:
- wer
model-index:
- name: Whisper Base EN
results: []
Whisper Base EN
This model is a fine-tuned version of 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