| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: wav2vec2-base_toy_train_data_augment_0.1 |
| | 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. --> |
| |
|
| | # wav2vec2-base_toy_train_data_augment_0.1 |
| | |
| | This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 3.3786 |
| | - Wer: 0.9954 |
| | |
| | ## 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: 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: 1000 |
| | - num_epochs: 20 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 3.1342 | 1.05 | 250 | 3.3901 | 0.9954 | |
| | | 3.0878 | 2.1 | 500 | 3.4886 | 0.9954 | |
| | | 3.0755 | 3.15 | 750 | 3.4616 | 0.9954 | |
| | | 3.0891 | 4.2 | 1000 | 3.5316 | 0.9954 | |
| | | 3.0724 | 5.25 | 1250 | 3.2608 | 0.9954 | |
| | | 3.0443 | 6.3 | 1500 | 3.3881 | 0.9954 | |
| | | 3.0421 | 7.35 | 1750 | 3.4507 | 0.9954 | |
| | | 3.0448 | 8.4 | 2000 | 3.4525 | 0.9954 | |
| | | 3.0455 | 9.45 | 2250 | 3.3342 | 0.9954 | |
| | | 3.0425 | 10.5 | 2500 | 3.3385 | 0.9954 | |
| | | 3.0457 | 11.55 | 2750 | 3.4411 | 0.9954 | |
| | | 3.0375 | 12.6 | 3000 | 3.4459 | 0.9954 | |
| | | 3.0459 | 13.65 | 3250 | 3.3883 | 0.9954 | |
| | | 3.0455 | 14.7 | 3500 | 3.3417 | 0.9954 | |
| | | 3.0524 | 15.75 | 3750 | 3.3908 | 0.9954 | |
| | | 3.0443 | 16.81 | 4000 | 3.3932 | 0.9954 | |
| | | 3.0446 | 17.86 | 4250 | 3.4052 | 0.9954 | |
| | | 3.0412 | 18.91 | 4500 | 3.3776 | 0.9954 | |
| | | 3.0358 | 19.96 | 4750 | 3.3786 | 0.9954 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.17.0 |
| | - Pytorch 1.11.0+cu102 |
| | - Datasets 2.0.0 |
| | - Tokenizers 0.11.6 |
| | |
