| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: facebook/hubert-base-ls960 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: hubert-custom |
| | 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. --> |
| |
|
| | # hubert-custom |
| |
|
| | This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.6927 |
| | - Accuracy: 0.5156 |
| |
|
| | ## 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: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 30 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-------:|:----:|:---------------:|:--------:| |
| | | 0.6835 | 2.7778 | 100 | 0.6809 | 0.5625 | |
| | | 0.6998 | 5.5556 | 200 | 0.6928 | 0.5156 | |
| | | 0.711 | 8.3333 | 300 | 0.7050 | 0.4844 | |
| | | 0.6965 | 11.1111 | 400 | 0.6932 | 0.4844 | |
| | | 0.6994 | 13.8889 | 500 | 0.7030 | 0.4844 | |
| | | 0.7002 | 16.6667 | 600 | 0.6927 | 0.5156 | |
| | | 0.6982 | 19.4444 | 700 | 0.6935 | 0.4844 | |
| | | 0.6981 | 22.2222 | 800 | 0.6928 | 0.5156 | |
| | | 0.6942 | 25.0 | 900 | 0.6923 | 0.5156 | |
| | | 0.6951 | 27.7778 | 1000 | 0.6927 | 0.5156 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.51.1 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.5.0 |
| | - Tokenizers 0.21.1 |
| |
|
