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wav2vec2-large-robust-ft-libri-960h-finetuned-ravdess-v3

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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-large-robust-ft-libri-960h
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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: wav2vec2-large-robust-ft-libri-960h-finetuned-ravdess-v3
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+ results: []
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+ ---
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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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+
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+ # wav2vec2-large-robust-ft-libri-960h-finetuned-ravdess-v3
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-robust-ft-libri-960h](https://huggingface.co/facebook/wav2vec2-large-robust-ft-libri-960h) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9736
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+ - Accuracy: 0.6354
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.0795 | 1.0 | 18 | 2.0783 | 0.1007 |
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+ | 2.0703 | 2.0 | 36 | 2.0743 | 0.1181 |
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+ | 2.062 | 3.0 | 54 | 2.0632 | 0.1597 |
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+ | 2.0444 | 4.0 | 72 | 2.0439 | 0.1910 |
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+ | 2.0031 | 5.0 | 90 | 1.9762 | 0.2778 |
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+ | 1.9632 | 6.0 | 108 | 1.8421 | 0.3576 |
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+ | 1.8249 | 7.0 | 126 | 1.7072 | 0.3889 |
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+ | 1.6733 | 8.0 | 144 | 1.5729 | 0.3819 |
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+ | 1.5452 | 9.0 | 162 | 1.4826 | 0.4201 |
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+ | 1.4479 | 10.0 | 180 | 1.4214 | 0.4236 |
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+ | 1.443 | 11.0 | 198 | 1.3441 | 0.4340 |
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+ | 1.3341 | 12.0 | 216 | 1.3241 | 0.5 |
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+ | 1.2697 | 13.0 | 234 | 1.2810 | 0.5069 |
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+ | 1.2348 | 14.0 | 252 | 1.2349 | 0.5069 |
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+ | 1.1785 | 15.0 | 270 | 1.1948 | 0.5208 |
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+ | 1.1687 | 16.0 | 288 | 1.1831 | 0.5451 |
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+ | 1.1168 | 17.0 | 306 | 1.1481 | 0.5764 |
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+ | 1.0975 | 18.0 | 324 | 1.1342 | 0.5764 |
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+ | 1.0491 | 19.0 | 342 | 1.1138 | 0.6146 |
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+ | 1.033 | 20.0 | 360 | 1.0800 | 0.6146 |
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+ | 1.0523 | 21.0 | 378 | 1.0678 | 0.6146 |
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+ | 1.0136 | 22.0 | 396 | 1.0472 | 0.6111 |
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+ | 0.9777 | 23.0 | 414 | 1.0175 | 0.6111 |
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+ | 1.0007 | 24.0 | 432 | 1.0703 | 0.6215 |
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+ | 0.9584 | 25.0 | 450 | 0.9935 | 0.6181 |
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+ | 0.9102 | 26.0 | 468 | 0.9736 | 0.6354 |
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+ | 0.9101 | 27.0 | 486 | 0.9758 | 0.6285 |
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+ | 0.9405 | 28.0 | 504 | 0.9659 | 0.6319 |
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+ | 0.9366 | 29.0 | 522 | 0.9719 | 0.625 |
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+ | 0.9498 | 30.0 | 540 | 0.9713 | 0.6215 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3