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balanced-augmented-bert-gest-pred-seqeval-partialmatch-2

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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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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: balanced-augmented-bert-gest-pred-seqeval-partialmatch-2
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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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+ # balanced-augmented-bert-gest-pred-seqeval-partialmatch-2
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+
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+ This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4046
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+ - Precision: 0.9383
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+ - Recall: 0.9205
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+ - F1: 0.9237
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+ - Accuracy: 0.9098
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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: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 3.1239 | 1.0 | 52 | 2.5758 | 0.1906 | 0.1293 | 0.1175 | 0.3121 |
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+ | 2.1363 | 2.0 | 104 | 1.7477 | 0.4478 | 0.4505 | 0.4151 | 0.5576 |
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+ | 1.5182 | 3.0 | 156 | 1.3113 | 0.7051 | 0.6014 | 0.5633 | 0.6507 |
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+ | 1.0948 | 4.0 | 208 | 0.9763 | 0.7361 | 0.6854 | 0.6695 | 0.7183 |
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+ | 0.7591 | 5.0 | 260 | 0.7834 | 0.7900 | 0.7905 | 0.7726 | 0.7869 |
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+ | 0.5168 | 6.0 | 312 | 0.5764 | 0.8775 | 0.8569 | 0.8479 | 0.8550 |
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+ | 0.3609 | 7.0 | 364 | 0.5130 | 0.9055 | 0.8857 | 0.8815 | 0.8760 |
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+ | 0.2538 | 8.0 | 416 | 0.4872 | 0.9106 | 0.8828 | 0.8865 | 0.8805 |
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+ | 0.1898 | 9.0 | 468 | 0.3937 | 0.9219 | 0.9070 | 0.9076 | 0.8996 |
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+ | 0.1343 | 10.0 | 520 | 0.3897 | 0.9271 | 0.9016 | 0.9095 | 0.9010 |
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+ | 0.1053 | 11.0 | 572 | 0.3900 | 0.9309 | 0.9085 | 0.9143 | 0.9030 |
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+ | 0.0788 | 12.0 | 624 | 0.3649 | 0.9322 | 0.9236 | 0.9235 | 0.9138 |
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+ | 0.0643 | 13.0 | 676 | 0.4147 | 0.9293 | 0.9073 | 0.9122 | 0.9045 |
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+ | 0.0501 | 14.0 | 728 | 0.4788 | 0.9369 | 0.9205 | 0.9200 | 0.9054 |
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+ | 0.0424 | 15.0 | 780 | 0.4003 | 0.9346 | 0.9180 | 0.9197 | 0.9094 |
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+ | 0.0376 | 16.0 | 832 | 0.3686 | 0.9373 | 0.9261 | 0.9274 | 0.9182 |
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+ | 0.0317 | 17.0 | 884 | 0.4025 | 0.9360 | 0.9199 | 0.9223 | 0.9098 |
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+ | 0.0288 | 18.0 | 936 | 0.4484 | 0.9406 | 0.9212 | 0.9239 | 0.9098 |
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+ | 0.0282 | 19.0 | 988 | 0.4004 | 0.9377 | 0.9207 | 0.9238 | 0.9094 |
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+ | 0.0256 | 20.0 | 1040 | 0.4046 | 0.9383 | 0.9205 | 0.9237 | 0.9098 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.27.3
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+ - Pytorch 1.13.1+cu116
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+ - Datasets 2.10.1
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+ - Tokenizers 0.13.2