| --- |
| license: apache-2.0 |
| base_model: facebook/wav2vec2-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: mydata-sentence |
| 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. --> |
|
|
| # mydata-sentence |
|
|
| This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7519 |
| - Accuracy: 0.4615 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 15 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.7048 | 1.0 | 4 | 0.7079 | 0.3846 | |
| | 0.6478 | 2.0 | 8 | 0.7239 | 0.3846 | |
| | 0.7242 | 3.0 | 12 | 0.7464 | 0.3846 | |
| | 0.5978 | 4.0 | 16 | 0.7460 | 0.4615 | |
| | 0.7061 | 5.0 | 20 | 0.7460 | 0.4615 | |
| | 0.7089 | 6.0 | 24 | 0.7377 | 0.4615 | |
| | 0.5751 | 7.0 | 28 | 0.7324 | 0.4615 | |
| | 0.5799 | 8.0 | 32 | 0.7365 | 0.4615 | |
| | 0.563 | 9.0 | 36 | 0.7477 | 0.4615 | |
| | 0.555 | 10.0 | 40 | 0.7562 | 0.4615 | |
| | 0.5227 | 11.0 | 44 | 0.7632 | 0.4615 | |
| | 0.6701 | 12.0 | 48 | 0.7590 | 0.4615 | |
| | 0.5219 | 13.0 | 52 | 0.7540 | 0.4615 | |
| | 0.5003 | 14.0 | 56 | 0.7526 | 0.4615 | |
| | 0.488 | 15.0 | 60 | 0.7519 | 0.4615 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.37.2 |
| - Pytorch 2.2.0 |
| - Datasets 2.12.0 |
| - Tokenizers 0.15.1 |
| |
