| --- |
| license: apache-2.0 |
| base_model: SpeechFlow/spoken_language_identification |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: AudioClassification |
| 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. --> |
|
|
| # AudioClassification |
|
|
| 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: 0.9903 |
| - Accuracy: 0.35 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 128 |
| - 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 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.6783 | 0.98 | 11 | 1.0771 | 0.21 | |
| | 0.6614 | 1.96 | 22 | 0.9514 | 0.25 | |
| | 0.6628 | 2.93 | 33 | 0.9843 | 0.28 | |
| | 0.6629 | 4.0 | 45 | 1.0408 | 0.27 | |
| | 0.6583 | 4.98 | 56 | 1.0061 | 0.29 | |
| | 0.6623 | 5.96 | 67 | 1.0227 | 0.31 | |
| | 0.6613 | 6.93 | 78 | 1.0398 | 0.30 | |
| | 0.6635 | 8.0 | 90 | 1.0085 | 0.29 | |
| | 0.6577 | 8.98 | 101 | 0.9842 | 0.34 | |
| | 0.6629 | 9.78 | 110 | 0.9903 | 0.35 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.34.1 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
