metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-speech-small
results: []
whisper-speech-small
This model is a fine-tuned version of openai/whisper-small on the Google speech dataset. It achieves the following results on the evaluation set:
- Loss: 0.0021
- Wer: 0.3861
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 3000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0095 | 0.2 | 250 | 0.0042 | 0.7239 |
| 0.0068 | 0.4 | 500 | 0.0051 | 1.0135 |
| 0.0045 | 0.6 | 750 | 0.0021 | 0.3861 |
| 0.0056 | 0.8 | 1000 | 0.0018 | 1.5927 |
| 0.0021 | 1.0 | 1250 | 0.0023 | 8.8803 |
| 0.0081 | 1.2 | 1500 | 0.0033 | 2.0270 |
| 0.0056 | 1.4 | 1750 | 0.0023 | 6.1293 |
| 0.0028 | 1.6 | 2000 | 0.0017 | 0.8687 |
| 0.0064 | 1.81 | 2250 | 0.0011 | 0.8687 |
| 0.0005 | 2.01 | 2500 | 0.0014 | 2.0270 |
| 0.0015 | 2.21 | 2750 | 0.0013 | 1.4961 |
| 0.0012 | 2.41 | 3000 | 0.0014 | 1.8822 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3