metadata
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-mse-take-3
results: []
libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-mse-take-3
This model is a fine-tuned version of rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-mse on the None dataset. It achieves the following results on the evaluation set:
- Loss: 28.9263
- Wer: 0.3301
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: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 291.1088 | 0.22 | 400 | 28.4207 | 0.3362 |
| 284.1968 | 0.45 | 800 | 28.1458 | 0.3314 |
| 288.1414 | 0.67 | 1200 | 28.1397 | 0.3326 |
| 290.0272 | 0.9 | 1600 | 28.4186 | 0.3323 |
| 287.3224 | 1.12 | 2000 | 28.3548 | 0.3283 |
| 279.1482 | 1.35 | 2400 | 28.5373 | 0.3309 |
| 285.8217 | 1.57 | 2800 | 28.4447 | 0.3301 |
| 282.9265 | 1.79 | 3200 | 28.5379 | 0.3365 |
| 292.6254 | 2.02 | 3600 | 28.2632 | 0.3299 |
| 279.215 | 2.24 | 4000 | 28.9263 | 0.3301 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0