<!-- 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. -->
libri-finetune
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 349.4102
- Wer: 0.8141
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
13179.94 | 2.99 | 400 | 5612.7529 | 1.0 |
6948.38 | 5.97 | 800 | 1633.0823 | 0.9563 |
2144.6125 | 8.96 | 1200 | 578.3821 | 0.8487 |
1293.3905 | 11.94 | 1600 | 448.8980 | 0.8405 |
955.5785 | 14.93 | 2000 | 403.0979 | 0.8327 |
843.732 | 17.91 | 2400 | 374.1770 | 0.8220 |
739.1473 | 20.9 | 2800 | 360.7842 | 0.8179 |
651.852 | 23.88 | 3200 | 353.6803 | 0.8159 |
658.5995 | 26.87 | 3600 | 350.6870 | 0.8099 |
608.4441 | 29.85 | 4000 | 349.4102 | 0.8141 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1