libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-5
This model is a fine-tuned version of rohitp1/libri-smallw2v2-no-copy-mse-alpha-0.75-T-1-take-3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 30.3050
- Wer: 0.2650
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: 0.002
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
239.4865 | 1.12 | 400 | 31.0836 | 0.2908 |
210.2046 | 2.25 | 800 | 29.7831 | 0.2742 |
195.0478 | 3.37 | 1200 | 28.8794 | 0.2636 |
188.8096 | 4.49 | 1600 | 28.7458 | 0.2600 |
183.6592 | 5.62 | 2000 | 29.1159 | 0.2573 |
181.5025 | 6.74 | 2400 | 29.0081 | 0.2564 |
181.9954 | 7.86 | 2800 | 28.7132 | 0.2588 |
181.8548 | 8.99 | 3200 | 29.3207 | 0.2630 |
186.2524 | 10.11 | 3600 | 29.9119 | 0.2593 |
188.3838 | 11.24 | 4000 | 30.2963 | 0.2627 |
192.2623 | 12.36 | 4400 | 30.3050 | 0.2650 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0
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