metadata
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-4
results: []
libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-4
This model is a fine-tuned version of rohitp1/libri-alpha-0.75-Temp-1-attention-3-layers-distil-with-6-layers-att-take-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 37.5364
- Wer: 0.3334
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: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- 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 |
---|---|---|---|---|
43.7806 | 0.9 | 400 | 41.3073 | 0.2570 |
48.6549 | 1.8 | 800 | 41.8945 | 0.2740 |
57.4209 | 2.7 | 1200 | 39.9947 | 0.2872 |
68.8449 | 3.59 | 1600 | 39.4528 | 0.3059 |
79.4299 | 4.49 | 2000 | 38.9575 | 0.3179 |
93.0514 | 5.39 | 2400 | 37.5364 | 0.3334 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.7.1
- Tokenizers 0.11.0