whisper-small-mn-11
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0138
- Wer: 51.9664
- Cer: 19.8770
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: 32
- 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: 500
- training_steps: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0025 | 32.26 | 1000 | 0.8913 | 53.6214 | 20.6866 |
| 0.0007 | 64.52 | 2000 | 0.9326 | 52.1685 | 19.5991 |
| 0.0001 | 96.77 | 3000 | 1.0138 | 51.9664 | 19.8770 |
| 0.0001 | 129.03 | 4000 | 1.0639 | 52.1248 | 19.9178 |
| 0.0 | 161.29 | 5000 | 1.1236 | 52.0428 | 19.9652 |
| 0.0 | 193.55 | 6000 | 1.1677 | 52.4634 | 20.0351 |
| 0.0 | 225.81 | 7000 | 1.2224 | 52.5836 | 20.1258 |
| 0.0 | 258.06 | 8000 | 1.2633 | 52.7310 | 20.2073 |
| 0.0 | 290.32 | 9000 | 1.3152 | 52.8184 | 20.2273 |
| 0.0 | 322.58 | 10000 | 1.3530 | 52.9495 | 20.3080 |
| 0.0 | 354.84 | 11000 | 1.3995 | 53.0260 | 20.3088 |
| 0.0 | 387.1 | 12000 | 1.4306 | 52.9878 | 20.2057 |
| 0.0 | 419.35 | 13000 | 1.4674 | 52.9714 | 20.3113 |
| 0.0 | 451.61 | 14000 | 1.4859 | 52.9386 | 20.2947 |
| 0.0 | 483.87 | 15000 | 1.4994 | 52.9768 | 20.3280 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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Datasets used to train bayartsogt/whisper-small-mn-11
Evaluation results
- Wer on Common Voice 11.0test set self-reported51.966
- Cer on Common Voice 11.0test set self-reported19.877