<!-- 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 Small Assamese
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 as dataset. It achieves the following results on the evaluation set:
- Loss: 0.6033
- Wer: 35.4990
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 40
- training_steps: 400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.0676 | 3.01 | 50 | 0.6487 | 62.5338 |
| 0.2252 | 6.03 | 100 | 0.3487 | 36.4916 |
| 0.0787 | 9.04 | 150 | 0.3934 | 35.6434 |
| 0.0178 | 13.01 | 200 | 0.5057 | 36.0043 |
| 0.0048 | 16.02 | 250 | 0.5589 | 35.8239 |
| 0.0022 | 19.04 | 300 | 0.5882 | 35.7336 |
| 0.0015 | 23.01 | 350 | 0.5985 | 35.5712 |
| 0.0013 | 26.02 | 400 | 0.6033 | 35.4990 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
