| | --- |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - librispeech_asr |
| | model-index: |
| | - name: '' |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # |
| |
|
| | This model was trained from scratch on the librispeech_asr dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 6.9251 |
| | - Wer: 1.7858 |
| | |
| | ## 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: 3e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 16 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 3.0 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 6.6487 | 0.28 | 500 | 6.8354 | 1.4719 | |
| | | 6.5662 | 0.56 | 1000 | 6.7877 | 0.9371 | |
| | | 6.4309 | 0.84 | 1500 | 6.7640 | 1.1317 | |
| | | 6.7123 | 1.12 | 2000 | 6.7907 | 1.9354 | |
| | | 6.7547 | 1.4 | 2500 | 6.7830 | 1.8854 | |
| | | 6.6726 | 1.68 | 3000 | 6.8211 | 1.9203 | |
| | | 6.6538 | 1.96 | 3500 | 6.8444 | 1.8235 | |
| | | 6.5693 | 2.24 | 4000 | 6.8873 | 1.8606 | |
| | | 6.7234 | 2.52 | 4500 | 6.8649 | 1.8126 | |
| | | 6.5104 | 2.8 | 5000 | 6.9251 | 1.7858 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.17.0.dev0 |
| | - Pytorch 1.10.2+cu113 |
| | - Datasets 1.18.3 |
| | - Tokenizers 0.11.0 |
| | |
