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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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- f1 |
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model-index: |
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- name: bert-base-uncased-finetuned-iemocap8 |
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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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# bert-base-uncased-finetuned-iemocap8 |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8968 |
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- Accuracy: 0.6654 |
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- F1: 0.6723 |
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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: 4.319412088241492e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 32 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| No log | 1.0 | 51 | 1.0531 | 0.5597 | 0.5655 | |
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| 1.0284 | 2.0 | 102 | 0.9370 | 0.6227 | 0.6304 | |
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| 1.0284 | 3.0 | 153 | 0.8796 | 0.6722 | 0.6765 | |
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| 0.4432 | 4.0 | 204 | 0.9785 | 0.6654 | 0.6727 | |
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| 0.4432 | 5.0 | 255 | 1.0664 | 0.6586 | 0.6634 | |
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| 0.2492 | 6.0 | 306 | 1.1291 | 0.6499 | 0.6606 | |
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| 0.2492 | 7.0 | 357 | 1.1847 | 0.6702 | 0.6777 | |
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| 0.1707 | 8.0 | 408 | 1.4084 | 0.6508 | 0.6534 | |
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| 0.1707 | 9.0 | 459 | 1.3468 | 0.6702 | 0.6762 | |
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| 0.1461 | 10.0 | 510 | 1.4245 | 0.6634 | 0.6710 | |
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| 0.1461 | 11.0 | 561 | 1.4865 | 0.6499 | 0.6600 | |
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| 0.1262 | 12.0 | 612 | 1.4616 | 0.6576 | 0.6656 | |
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| 0.1262 | 13.0 | 663 | 1.5335 | 0.6663 | 0.6711 | |
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| 0.1203 | 14.0 | 714 | 1.4855 | 0.6731 | 0.6806 | |
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| 0.1203 | 15.0 | 765 | 1.5825 | 0.6712 | 0.6792 | |
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| 0.1023 | 16.0 | 816 | 1.7145 | 0.6731 | 0.6794 | |
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| 0.1023 | 17.0 | 867 | 1.6676 | 0.6751 | 0.6823 | |
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| 0.0976 | 18.0 | 918 | 1.8013 | 0.6693 | 0.6719 | |
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| 0.0976 | 19.0 | 969 | 1.7192 | 0.6673 | 0.6755 | |
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| 0.0937 | 20.0 | 1020 | 1.7837 | 0.6654 | 0.6731 | |
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| 0.0937 | 21.0 | 1071 | 1.7779 | 0.6760 | 0.6831 | |
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| 0.0901 | 22.0 | 1122 | 1.8352 | 0.6615 | 0.6687 | |
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| 0.0901 | 23.0 | 1173 | 1.8601 | 0.6596 | 0.6656 | |
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| 0.0844 | 24.0 | 1224 | 1.9129 | 0.6625 | 0.6719 | |
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| 0.0844 | 25.0 | 1275 | 1.8507 | 0.6731 | 0.6784 | |
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| 0.0829 | 26.0 | 1326 | 1.8582 | 0.6673 | 0.6735 | |
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| 0.0829 | 27.0 | 1377 | 1.8670 | 0.6770 | 0.6825 | |
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| 0.0839 | 28.0 | 1428 | 1.8763 | 0.6741 | 0.6800 | |
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| 0.0839 | 29.0 | 1479 | 1.8925 | 0.6702 | 0.6769 | |
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| 0.0802 | 30.0 | 1530 | 1.8968 | 0.6654 | 0.6723 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.0 |
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- Tokenizers 0.13.2 |
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