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--- |
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license: apache-2.0 |
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tags: |
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- Speech-Emotion-Recognition |
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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-xlsr-Shemo-Ravdess-4EMO |
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results: [] |
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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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# Wav2vec2-xlsr-Shemo-Ravdess-4EMO |
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This model is a fine-tuned version of [makhataei/Wav2vec2-xlsr-Shemo-Ravdess-4EMO](https://huggingface.co/makhataei/Wav2vec2-xlsr-Shemo-Ravdess-4EMO) on the minoosh/shEMO dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9089 |
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- Accuracy: 0.6712 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 35 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.9106 | 1.0 | 250 | 1.0288 | 0.6259 | |
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| 0.8205 | 2.0 | 500 | 0.9426 | 0.6576 | |
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| 0.7767 | 3.0 | 750 | 0.9707 | 0.6553 | |
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| 0.803 | 4.0 | 1000 | 0.9698 | 0.6644 | |
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| 0.7489 | 5.0 | 1250 | 0.9583 | 0.6463 | |
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| 0.7734 | 6.0 | 1500 | 0.9138 | 0.6757 | |
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| 0.7603 | 7.0 | 1750 | 0.8905 | 0.6712 | |
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| 0.7741 | 8.0 | 2000 | 0.9169 | 0.6599 | |
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| 0.7569 | 9.0 | 2250 | 0.9369 | 0.6417 | |
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| 0.7854 | 10.0 | 2500 | 0.9256 | 0.6599 | |
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| 0.7572 | 11.0 | 2750 | 0.9320 | 0.6621 | |
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| 0.7537 | 12.0 | 3000 | 0.8960 | 0.6825 | |
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| 0.745 | 13.0 | 3250 | 0.9495 | 0.6599 | |
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| 0.7598 | 14.0 | 3500 | 0.9196 | 0.6667 | |
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| 0.7536 | 15.0 | 3750 | 0.9464 | 0.6599 | |
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| 0.7428 | 16.0 | 4000 | 0.9407 | 0.6485 | |
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| 0.757 | 17.0 | 4250 | 0.9251 | 0.6689 | |
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| 0.7694 | 18.0 | 4500 | 0.9246 | 0.6576 | |
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| 0.7501 | 19.0 | 4750 | 0.9283 | 0.6621 | |
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| 0.7464 | 20.0 | 5000 | 0.9333 | 0.6531 | |
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| 0.7569 | 21.0 | 5250 | 0.9062 | 0.6667 | |
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| 0.745 | 22.0 | 5500 | 0.9569 | 0.6485 | |
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| 0.7404 | 23.0 | 5750 | 0.9062 | 0.6667 | |
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| 0.7384 | 24.0 | 6000 | 0.8948 | 0.6780 | |
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| 0.7524 | 25.0 | 6250 | 0.9296 | 0.6599 | |
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| 0.7574 | 26.0 | 6500 | 0.8925 | 0.6825 | |
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| 0.7876 | 27.0 | 6750 | 0.9061 | 0.6712 | |
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| 0.7692 | 28.0 | 7000 | 0.9319 | 0.6508 | |
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| 0.7352 | 29.0 | 7250 | 0.9145 | 0.6644 | |
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| 0.7496 | 30.0 | 7500 | 0.9068 | 0.6735 | |
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| 0.7406 | 31.0 | 7750 | 0.9024 | 0.6735 | |
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| 0.7334 | 32.0 | 8000 | 0.9231 | 0.6576 | |
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| 0.761 | 33.0 | 8250 | 0.9073 | 0.6712 | |
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| 0.7476 | 34.0 | 8500 | 0.9097 | 0.6667 | |
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| 0.7868 | 35.0 | 8750 | 0.9089 | 0.6712 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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