| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: wav2vec2-base_toy_train_data_augmented |
| | 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_augmented |
| |
|
| | 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: 1.0238 |
| | - Wer: 0.6969 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | | 3.12 | 1.05 | 250 | 3.3998 | 0.9982 | |
| | | 3.0727 | 2.1 | 500 | 3.1261 | 0.9982 | |
| | | 1.9729 | 3.15 | 750 | 1.4868 | 0.9464 | |
| | | 1.3213 | 4.2 | 1000 | 1.2598 | 0.8833 | |
| | | 1.0508 | 5.25 | 1250 | 1.0014 | 0.8102 | |
| | | 0.8483 | 6.3 | 1500 | 0.9475 | 0.7944 | |
| | | 0.7192 | 7.35 | 1750 | 0.9493 | 0.7686 | |
| | | 0.6447 | 8.4 | 2000 | 0.9872 | 0.7573 | |
| | | 0.6064 | 9.45 | 2250 | 0.9587 | 0.7447 | |
| | | 0.5384 | 10.5 | 2500 | 0.9332 | 0.7320 | |
| | | 0.4985 | 11.55 | 2750 | 0.9926 | 0.7315 | |
| | | 0.4643 | 12.6 | 3000 | 1.0008 | 0.7292 | |
| | | 0.4565 | 13.65 | 3250 | 0.9522 | 0.7171 | |
| | | 0.449 | 14.7 | 3500 | 0.9685 | 0.7140 | |
| | | 0.4307 | 15.75 | 3750 | 1.0080 | 0.7077 | |
| | | 0.4239 | 16.81 | 4000 | 0.9950 | 0.7023 | |
| | | 0.389 | 17.86 | 4250 | 1.0260 | 0.7007 | |
| | | 0.3471 | 18.91 | 4500 | 1.0012 | 0.6966 | |
| | | 0.3276 | 19.96 | 4750 | 1.0238 | 0.6969 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.17.0 |
| | - Pytorch 1.11.0+cu102 |
| | - Datasets 2.0.0 |
| | - Tokenizers 0.11.6 |
| |
|
