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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec-best-CREMA-sentiment-analysis-best3 |
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results: [] |
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datasets: |
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- Supreeta03/CREMA-audioData |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec-best-CREMA-sentiment-analysis-best3 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on [Supreeta03/CREMA-audioData](https://huggingface.co/datasets/Supreeta03/CREMA-audioData). |
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It achieves the following results on the evaluation set: |
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- top2 Accuracy: 0.7824 |
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- Loss: 1.1563 |
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- Accuracy: 0.5601 |
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## Model description |
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Fine tuned from [facebook/wav2vec2-base] for performing sentiment analysis on audio data. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Top2 Accuracy | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:-------------:|:---------------:|:--------:| |
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| 1.7555 | 0.99 | 37 | 0.5281 | 1.7048 | 0.2905 | |
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| 1.5612 | 1.99 | 74 | 0.5819 | 1.5406 | 0.3493 | |
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| 1.4333 | 2.98 | 111 | 0.6373 | 1.4668 | 0.3778 | |
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| 1.3933 | 4.0 | 149 | 0.6809 | 1.3798 | 0.4450 | |
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| 1.3418 | 4.99 | 186 | 0.7045 | 1.3120 | 0.4719 | |
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| 1.2238 | 5.99 | 223 | 0.7263 | 1.2718 | 0.4979 | |
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| 1.1896 | 6.98 | 260 | 0.7313 | 1.2430 | 0.5113 | |
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| 1.1501 | 8.0 | 298 | 0.7296 | 1.2631 | 0.5088 | |
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| 1.1052 | 8.99 | 335 | 0.7506 | 1.2462 | 0.5097 | |
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| 1.068 | 9.99 | 372 | 0.7641 | 1.1822 | 0.5399 | |
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| 1.0594 | 10.98 | 409 | 0.7590 | 1.1700 | 0.5575 | |
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| 0.9519 | 12.0 | 447 | 0.7733 | 1.1465 | 0.5516 | |
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| 0.9513 | 12.99 | 484 | 0.7918 | 1.1428 | 0.5676 | |
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| 0.9324 | 13.99 | 521 | 0.7666 | 1.1721 | 0.5634 | |
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| 0.9173 | 14.98 | 558 | 0.7825 | 1.1494 | 0.5584 | |
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| 0.8781 | 16.0 | 596 | 0.7918 | 1.1468 | 0.5718 | |
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| 0.8627 | 16.99 | 633 | 0.7775 | 1.1554 | 0.5575 | |
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| 0.83 | 17.99 | 670 | 0.7817 | 1.1438 | 0.5718 | |
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| 0.8305 | 18.98 | 707 | 0.7935 | 1.1323 | 0.5760 | |
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| 0.8314 | 19.87 | 740 | 0.7851 | 1.1341 | 0.5726 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
