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

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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
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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
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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: 0.9263
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+ - Precision: 0.8443
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+ - Recall: 0.8275
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+ - F1: 0.8298
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+ - Accuracy: 0.8139
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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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+ | 3.3729 | 1.0 | 32 | 2.8438 | 0.0806 | 0.0549 | 0.0294 | 0.1986 |
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+ | 2.7169 | 2.0 | 64 | 2.2356 | 0.4355 | 0.2940 | 0.2982 | 0.4307 |
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+ | 2.0107 | 3.0 | 96 | 1.7202 | 0.6950 | 0.5187 | 0.5245 | 0.5698 |
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+ | 1.4085 | 4.0 | 128 | 1.3703 | 0.7994 | 0.6487 | 0.6499 | 0.6582 |
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+ | 0.9974 | 5.0 | 160 | 1.1172 | 0.8205 | 0.7349 | 0.7514 | 0.7156 |
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+ | 0.6996 | 6.0 | 192 | 1.0020 | 0.8220 | 0.7550 | 0.7684 | 0.7451 |
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+ | 0.492 | 7.0 | 224 | 0.9132 | 0.8203 | 0.7626 | 0.7722 | 0.7549 |
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+ | 0.3593 | 8.0 | 256 | 0.8785 | 0.8475 | 0.8042 | 0.8135 | 0.7921 |
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+ | 0.2618 | 9.0 | 288 | 0.8383 | 0.8395 | 0.8135 | 0.8199 | 0.7999 |
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+ | 0.1928 | 10.0 | 320 | 0.8410 | 0.8433 | 0.8165 | 0.8240 | 0.8014 |
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+ | 0.1541 | 11.0 | 352 | 0.8382 | 0.8478 | 0.8224 | 0.8293 | 0.8118 |
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+ | 0.1216 | 12.0 | 384 | 0.8667 | 0.8259 | 0.8253 | 0.8210 | 0.8046 |
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+ | 0.096 | 13.0 | 416 | 0.8726 | 0.8471 | 0.8253 | 0.8301 | 0.8133 |
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+ | 0.0767 | 14.0 | 448 | 0.8826 | 0.8475 | 0.8307 | 0.8330 | 0.8102 |
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+ | 0.0696 | 15.0 | 480 | 0.8964 | 0.8411 | 0.8285 | 0.8303 | 0.8149 |
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+ | 0.057 | 16.0 | 512 | 0.9194 | 0.8365 | 0.8292 | 0.8289 | 0.8097 |
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+ | 0.0514 | 17.0 | 544 | 0.9085 | 0.8502 | 0.8277 | 0.8326 | 0.8118 |
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+ | 0.0468 | 18.0 | 576 | 0.9261 | 0.8345 | 0.8250 | 0.8243 | 0.8092 |
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+ | 0.0437 | 19.0 | 608 | 0.9279 | 0.8394 | 0.8258 | 0.8270 | 0.8118 |
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+ | 0.0414 | 20.0 | 640 | 0.9263 | 0.8443 | 0.8275 | 0.8298 | 0.8139 |
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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