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bert-base-uncased-finetuned-iemocap8

Text Classification
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PyTorch
bert
Generated from Trainer
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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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+
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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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+ # bert-base-uncased-finetuned-iemocap8
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+
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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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+
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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: 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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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