| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: ft-wav2vec2-with-minds |
| | 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. --> |
| |
|
| | # ft-wav2vec2-with-minds |
| |
|
| | This model was trained from scratch on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0333 |
| | - Accuracy: 0.9972 |
| |
|
| | ## 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: 120 |
| | - eval_batch_size: 120 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 4 |
| | - total_train_batch_size: 480 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 10 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 4.6092 | 1.0 | 9 | 2.4860 | 0.4311 | |
| | | 1.4641 | 2.0 | 18 | 0.5758 | 0.7826 | |
| | | 0.5061 | 3.0 | 27 | 0.1966 | 0.9756 | |
| | | 0.2573 | 4.0 | 36 | 0.1038 | 0.9803 | |
| | | 0.1557 | 5.0 | 45 | 0.0671 | 0.9859 | |
| | | 0.1235 | 6.0 | 54 | 0.0333 | 0.9972 | |
| | | 0.0725 | 7.0 | 63 | 0.0334 | 0.9944 | |
| | | 0.0914 | 8.0 | 72 | 0.0279 | 0.9953 | |
| | | 0.1695 | 9.0 | 81 | 0.0276 | 0.9972 | |
| | | 0.1118 | 10.0 | 90 | 0.0290 | 0.9972 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.2 |
| | - Pytorch 1.12.1+cu116 |
| | - Datasets 2.15.0 |
| | - Tokenizers 0.15.2 |
| |
|
