| --- |
| license: apache-2.0 |
| base_model: facebook/hubert-base-ls960 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - shemo |
| metrics: |
| - f1 |
| model-index: |
| - name: results |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: shemo |
| type: shemo |
| config: clean |
| split: None |
| args: clean |
| metrics: |
| - name: F1 |
| type: f1 |
| value: 0.8335174497965196 |
| --- |
| |
| <!-- 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. --> |
|
|
| # results |
|
|
| This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the shemo dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6161 |
| - F1: 0.8335 |
|
|
| ## Labels description |
|
|
| - 0 : anger |
| - 1 : happiness |
| - 2 : neutral |
| - 3 : sadness |
|
|
| ## 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: 5e-05 |
| - 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: 500 |
| - num_epochs: 25 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 1.1127 | 1.0 | 154 | 0.9244 | 0.3968 | |
| | 0.6982 | 2.0 | 308 | 0.5642 | 0.6435 | |
| | 0.6246 | 3.0 | 462 | 0.5049 | 0.6273 | |
| | 0.5097 | 4.0 | 616 | 0.4282 | 0.7246 | |
| | 0.4496 | 5.0 | 770 | 0.3280 | 0.8158 | |
| | 0.4476 | 6.0 | 924 | 0.4663 | 0.7978 | |
| | 0.2212 | 7.0 | 1078 | 0.3253 | 0.8641 | |
| | 0.1548 | 8.0 | 1232 | 0.9445 | 0.7420 | |
| | 0.3829 | 9.0 | 1386 | 0.7194 | 0.7880 | |
| | 0.0773 | 10.0 | 1540 | 0.5301 | 0.8657 | |
| | 0.2481 | 11.0 | 1694 | 0.5321 | 0.8812 | |
| | 0.0597 | 12.0 | 1848 | 0.6161 | 0.8335 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.41.2 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.2 |
| - Tokenizers 0.19.1 |
|
|
