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balanced-augmented-bert-large-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-large-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-large-gest-pred-seqeval-partialmatch-2
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+
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+ This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5066
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+ - Precision: 0.9246
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+ - Recall: 0.9232
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+ - F1: 0.9156
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+ - Accuracy: 0.9045
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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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+ | 2.9285 | 1.0 | 52 | 2.4277 | 0.2289 | 0.1482 | 0.1320 | 0.3077 |
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+ | 1.9821 | 2.0 | 104 | 1.6710 | 0.5805 | 0.4849 | 0.4419 | 0.5576 |
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+ | 1.3372 | 3.0 | 156 | 1.1456 | 0.6591 | 0.6279 | 0.6073 | 0.6703 |
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+ | 0.8553 | 4.0 | 208 | 0.7989 | 0.7950 | 0.7956 | 0.7738 | 0.7864 |
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+ | 0.4964 | 5.0 | 260 | 0.6153 | 0.8422 | 0.8447 | 0.8281 | 0.8378 |
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+ | 0.2985 | 6.0 | 312 | 0.4399 | 0.9124 | 0.8982 | 0.8966 | 0.8814 |
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+ | 0.1825 | 7.0 | 364 | 0.4938 | 0.8936 | 0.9034 | 0.8883 | 0.8829 |
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+ | 0.1178 | 8.0 | 416 | 0.4713 | 0.9087 | 0.9188 | 0.9069 | 0.8912 |
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+ | 0.0812 | 9.0 | 468 | 0.4012 | 0.9108 | 0.9274 | 0.9130 | 0.9045 |
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+ | 0.0579 | 10.0 | 520 | 0.4695 | 0.9120 | 0.9132 | 0.9050 | 0.8942 |
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+ | 0.0345 | 11.0 | 572 | 0.5327 | 0.9196 | 0.9165 | 0.9083 | 0.8976 |
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+ | 0.0309 | 12.0 | 624 | 0.5243 | 0.9273 | 0.9207 | 0.9146 | 0.9025 |
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+ | 0.0234 | 13.0 | 676 | 0.5089 | 0.9271 | 0.9243 | 0.9165 | 0.8996 |
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+ | 0.0175 | 14.0 | 728 | 0.4750 | 0.9284 | 0.9258 | 0.9190 | 0.9059 |
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+ | 0.015 | 15.0 | 780 | 0.4891 | 0.9310 | 0.9277 | 0.9210 | 0.9079 |
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+ | 0.0109 | 16.0 | 832 | 0.5126 | 0.9240 | 0.9222 | 0.9153 | 0.9045 |
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+ | 0.0085 | 17.0 | 884 | 0.4512 | 0.9320 | 0.9315 | 0.9246 | 0.9123 |
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+ | 0.0077 | 18.0 | 936 | 0.5363 | 0.9241 | 0.9226 | 0.9149 | 0.9035 |
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+ | 0.0058 | 19.0 | 988 | 0.5033 | 0.9246 | 0.9232 | 0.9156 | 0.9045 |
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+ | 0.0062 | 20.0 | 1040 | 0.5066 | 0.9246 | 0.9232 | 0.9156 | 0.9045 |
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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