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update model card README.md

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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: BERT_token_classification_14PTC_basic_fixed
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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_token_classification_14PTC_basic_fixed
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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: 1.2901
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+ - Precision: 0.0593
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+ - Recall: 0.0755
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+ - F1: 0.0664
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+ - Accuracy: 0.7149
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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: 8
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+ - eval_batch_size: 8
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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: 10
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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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+ | 1.1822 | 1.0 | 664 | 0.9721 | 0.1063 | 0.0329 | 0.0502 | 0.7774 |
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+ | 0.9937 | 2.0 | 1328 | 0.9852 | 0.0607 | 0.0622 | 0.0614 | 0.7508 |
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+ | 0.8517 | 3.0 | 1992 | 0.9996 | 0.0572 | 0.0577 | 0.0574 | 0.7376 |
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+ | 0.5704 | 4.0 | 2656 | 1.0643 | 0.0545 | 0.0657 | 0.0596 | 0.7296 |
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+ | 0.514 | 5.0 | 3320 | 1.1014 | 0.0555 | 0.0648 | 0.0598 | 0.7318 |
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+ | 0.4757 | 6.0 | 3984 | 1.1413 | 0.0565 | 0.0568 | 0.0567 | 0.7356 |
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+ | 0.3538 | 7.0 | 4648 | 1.2095 | 0.0598 | 0.0764 | 0.0671 | 0.7171 |
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+ | 0.3326 | 8.0 | 5312 | 1.2463 | 0.0551 | 0.0728 | 0.0627 | 0.7081 |
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+ | 0.3158 | 9.0 | 5976 | 1.2557 | 0.0636 | 0.0764 | 0.0694 | 0.7258 |
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+ | 0.2676 | 10.0 | 6640 | 1.2901 | 0.0593 | 0.0755 | 0.0664 | 0.7149 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.30.2
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.13.3