Whisper Medium Bambara Fieldwork
This model is a fine-tuned version of openai/whisper-medium on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 4.0725
- Wer: 157.6004
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: 16
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 13532
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6342 | 1.03 | 1000 | 2.5810 | 159.5293 |
| 0.2873 | 3.03 | 2000 | 2.9513 | 159.1140 |
| 0.1461 | 5.02 | 3000 | 3.6833 | 158.3941 |
| 0.049 | 7.02 | 4000 | 4.0725 | 157.6004 |
| 0.0218 | 9.01 | 5000 | 4.2531 | 158.3664 |
| 0.0071 | 11.0 | 6000 | 4.5944 | 157.9972 |
| 0.0057 | 12.04 | 7000 | 4.6659 | 161.4952 |
| 0.0061 | 14.03 | 8000 | 4.9162 | 161.0614 |
| 0.0042 | 16.03 | 9000 | 5.0205 | 158.9848 |
| 0.0007 | 18.02 | 10000 | 5.1463 | 159.1970 |
| 0.0015 | 20.01 | 11000 | 5.2150 | 159.0401 |
| 0.0001 | 22.01 | 12000 | 5.3008 | 159.5478 |
| 0.0001 | 24.0 | 13000 | 5.3800 | 159.0309 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
- Downloads last month
- 1