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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: emotion_detection_model |
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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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# emotion_detection_model |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6542 |
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- Accuracy: 0.8291 |
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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: 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 | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.6124 | 0.99 | 70 | 1.5873 | 0.3984 | |
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| 1.2504 | 1.99 | 141 | 1.2053 | 0.5963 | |
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| 0.833 | 3.0 | 212 | 0.8178 | 0.7504 | |
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| 0.6633 | 4.0 | 283 | 0.7137 | 0.7783 | |
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| 0.5791 | 4.99 | 353 | 0.6395 | 0.7915 | |
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| 0.4472 | 5.99 | 424 | 0.6398 | 0.7968 | |
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| 0.378 | 7.0 | 495 | 0.5669 | 0.8145 | |
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| 0.2902 | 8.0 | 566 | 0.5777 | 0.8158 | |
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| 0.2621 | 8.99 | 636 | 0.6320 | 0.8074 | |
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| 0.231 | 9.99 | 707 | 0.6347 | 0.8149 | |
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| 0.174 | 11.0 | 778 | 0.6649 | 0.8096 | |
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| 0.1781 | 12.0 | 849 | 0.6180 | 0.8211 | |
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| 0.1566 | 12.99 | 919 | 0.6311 | 0.8211 | |
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| 0.1239 | 13.99 | 990 | 0.6322 | 0.8207 | |
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| 0.1223 | 15.0 | 1061 | 0.6443 | 0.8264 | |
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| 0.0988 | 16.0 | 1132 | 0.6424 | 0.8255 | |
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| 0.0866 | 16.99 | 1202 | 0.6542 | 0.8291 | |
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| 0.0661 | 17.99 | 1273 | 0.6748 | 0.8264 | |
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| 0.0815 | 19.0 | 1344 | 0.6723 | 0.8286 | |
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| 0.0595 | 19.79 | 1400 | 0.6865 | 0.8229 | |
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### Framework versions |
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- Transformers 4.37.0 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.1 |
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