Whisper Small Es - GoCloud
This model is a fine-tuned version of openai/whisper-small on the 30seg dataset. It achieves the following results on the evaluation set:
- Loss: 0.0028
- Wer: 0.0
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: 25
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2944 | 5.56 | 50 | 0.1392 | 79.6117 |
| 0.08 | 11.11 | 100 | 0.0569 | 46.0472 |
| 0.0204 | 16.67 | 150 | 0.0086 | 0.0 |
| 0.0028 | 22.22 | 200 | 0.0028 | 0.0 |
Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Downloads last month
- 8
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.