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pratyush_whisper_small_distil_libri360_enc_8_dec_6_batch_2_epoch_50
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9043
- Wer: 13.0427
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: 0.0005
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 512
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
6.8528 | 0.49 | 100 | 5.4707 | 94.5857 |
5.4115 | 0.98 | 200 | 4.7525 | 89.6667 |
4.44 | 1.48 | 300 | 2.5672 | 47.3154 |
2.71 | 1.97 | 400 | 2.0272 | 26.9788 |
2.2003 | 2.46 | 500 | 1.8737 | 20.2713 |
2.0566 | 2.95 | 600 | 1.8204 | 17.6620 |
1.9829 | 3.45 | 700 | 1.7948 | 16.2944 |
1.9501 | 3.94 | 800 | 1.7809 | 15.3891 |
1.9173 | 4.43 | 900 | 1.7755 | 15.0537 |
1.9025 | 4.93 | 1000 | 1.7754 | 14.7302 |
1.8847 | 5.42 | 1100 | 1.7820 | 14.6116 |
1.8776 | 5.91 | 1200 | 1.7795 | 14.1585 |
1.8661 | 6.4 | 1300 | 1.7807 | 13.9664 |
1.8647 | 6.9 | 1400 | 1.7841 | 13.9940 |
1.858 | 7.39 | 1500 | 1.7921 | 13.9489 |
1.8608 | 7.88 | 1600 | 1.7997 | 13.9269 |
1.858 | 8.37 | 1700 | 1.8084 | 13.9370 |
1.8621 | 8.87 | 1800 | 1.8160 | 13.8414 |
1.8633 | 9.36 | 1900 | 1.8221 | 13.9627 |
1.8663 | 9.85 | 2000 | 1.8259 | 14.0013 |
1.8667 | 10.34 | 2100 | 1.8429 | 13.9379 |
1.865 | 10.84 | 2200 | 1.8406 | 13.9011 |
1.8614 | 11.33 | 2300 | 1.8401 | 13.5887 |
1.8564 | 11.82 | 2400 | 1.8587 | 13.5739 |
1.8552 | 12.32 | 2500 | 1.8514 | 13.5620 |
1.8523 | 12.81 | 2600 | 1.8561 | 13.3295 |
1.8551 | 13.3 | 2700 | 1.8581 | 13.3148 |
1.8521 | 13.79 | 2800 | 1.8650 | 13.1594 |
1.8522 | 14.29 | 2900 | 1.8729 | 13.2385 |
1.8513 | 14.78 | 3000 | 1.8754 | 13.1778 |
1.8524 | 15.27 | 3100 | 1.8814 | 13.0611 |
1.8495 | 15.76 | 3200 | 1.8867 | 13.2504 |
1.8553 | 16.26 | 3300 | 1.8860 | 13.0942 |
1.8531 | 16.75 | 3400 | 1.8884 | 12.8175 |
1.8545 | 17.24 | 3500 | 1.9003 | 12.8598 |
1.8533 | 17.73 | 3600 | 1.8982 | 13.0381 |
1.8548 | 18.23 | 3700 | 1.9005 | 13.0299 |
1.8542 | 18.72 | 3800 | 1.9067 | 13.0289 |
1.8552 | 19.21 | 3900 | 1.9043 | 13.0427 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.0
- Tokenizers 0.11.0