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--- |
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license: apache-2.0 |
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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: resultsfinalgerman |
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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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# resultsfinalgerman |
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This model is a fine-tuned version of [padmalcom/wav2vec2-large-emotion-detection-german](https://huggingface.co/padmalcom/wav2vec2-large-emotion-detection-german) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6302 |
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- Accuracy: 0.6429 |
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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: 1e-05 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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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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| 0.7053 | 1.0 | 13 | 0.6971 | 0.3571 | |
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| 0.6994 | 2.0 | 26 | 0.6930 | 0.5714 | |
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| 0.686 | 3.0 | 39 | 0.6891 | 0.5714 | |
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| 0.6759 | 4.0 | 52 | 0.6889 | 0.5714 | |
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| 0.6865 | 5.0 | 65 | 0.6870 | 0.5714 | |
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| 0.6916 | 6.0 | 78 | 0.6847 | 0.5714 | |
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| 0.6764 | 7.0 | 91 | 0.6854 | 0.5714 | |
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| 0.6768 | 8.0 | 104 | 0.6869 | 0.5714 | |
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| 0.6546 | 9.0 | 117 | 0.6882 | 0.5714 | |
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| 0.6806 | 10.0 | 130 | 0.6875 | 0.5714 | |
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| 0.6742 | 11.0 | 143 | 0.6893 | 0.5714 | |
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| 0.6675 | 12.0 | 156 | 0.6897 | 0.5714 | |
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| 0.6762 | 13.0 | 169 | 0.6903 | 0.5714 | |
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| 0.6451 | 14.0 | 182 | 0.6920 | 0.5714 | |
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| 0.6641 | 15.0 | 195 | 0.6928 | 0.5714 | |
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| 0.634 | 16.0 | 208 | 0.6974 | 0.5714 | |
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| 0.6342 | 17.0 | 221 | 0.6983 | 0.5714 | |
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| 0.6526 | 18.0 | 234 | 0.6992 | 0.5714 | |
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| 0.6498 | 19.0 | 247 | 0.6926 | 0.5714 | |
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| 0.6293 | 20.0 | 260 | 0.6842 | 0.5714 | |
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| 0.5946 | 21.0 | 273 | 0.6833 | 0.5714 | |
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| 0.6281 | 22.0 | 286 | 0.6761 | 0.5 | |
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| 0.6084 | 23.0 | 299 | 0.6748 | 0.5 | |
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| 0.6055 | 24.0 | 312 | 0.6655 | 0.5 | |
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| 0.5806 | 25.0 | 325 | 0.6670 | 0.7143 | |
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| 0.62 | 26.0 | 338 | 0.6550 | 0.5714 | |
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| 0.5741 | 27.0 | 351 | 0.6578 | 0.7143 | |
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| 0.6261 | 28.0 | 364 | 0.6675 | 0.6429 | |
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| 0.5069 | 29.0 | 377 | 0.6661 | 0.6429 | |
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| 0.5526 | 30.0 | 390 | 0.6602 | 0.6429 | |
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| 0.5145 | 31.0 | 403 | 0.6545 | 0.6429 | |
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| 0.5634 | 32.0 | 416 | 0.6553 | 0.6429 | |
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| 0.4619 | 33.0 | 429 | 0.6493 | 0.6429 | |
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| 0.5694 | 34.0 | 442 | 0.6487 | 0.6429 | |
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| 0.5045 | 35.0 | 455 | 0.6436 | 0.6429 | |
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| 0.4623 | 36.0 | 468 | 0.6448 | 0.6429 | |
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| 0.5001 | 37.0 | 481 | 0.6465 | 0.6429 | |
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| 0.4779 | 38.0 | 494 | 0.6439 | 0.6429 | |
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| 0.4751 | 39.0 | 507 | 0.6329 | 0.6429 | |
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| 0.4426 | 40.0 | 520 | 0.6294 | 0.6429 | |
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| 0.4341 | 41.0 | 533 | 0.6270 | 0.6429 | |
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| 0.4282 | 42.0 | 546 | 0.6265 | 0.6429 | |
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| 0.4908 | 43.0 | 559 | 0.6269 | 0.6429 | |
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| 0.4073 | 44.0 | 572 | 0.6251 | 0.6429 | |
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| 0.4207 | 45.0 | 585 | 0.6261 | 0.6429 | |
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| 0.4757 | 46.0 | 598 | 0.6277 | 0.6429 | |
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| 0.4357 | 47.0 | 611 | 0.6294 | 0.6429 | |
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| 0.4473 | 48.0 | 624 | 0.6302 | 0.6429 | |
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| 0.4047 | 49.0 | 637 | 0.6302 | 0.6429 | |
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| 0.4881 | 50.0 | 650 | 0.6302 | 0.6429 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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