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Yepes_0.0001_0404_ES6

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: mit
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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: Yepes_0.0001_0404_ES6
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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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+ # Yepes_0.0001_0404_ES6
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+
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+ This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1207
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+ - Precision: 0.4902
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+ - Recall: 0.3743
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+ - F1: 0.4244
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+ - Accuracy: 0.9769
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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: 0.0001
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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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+ - training_steps: 2000
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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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+ | 0.4338 | 0.43 | 25 | 0.1979 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.2051 | 0.86 | 50 | 0.1923 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1601 | 1.29 | 75 | 0.1618 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1742 | 1.72 | 100 | 0.1400 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1506 | 2.16 | 125 | 0.1462 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1507 | 2.59 | 150 | 0.1516 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1566 | 3.02 | 175 | 0.1382 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1467 | 3.45 | 200 | 0.1360 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1492 | 3.88 | 225 | 0.1400 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1543 | 4.31 | 250 | 0.1364 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1435 | 4.74 | 275 | 0.1384 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1369 | 5.17 | 300 | 0.1282 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1284 | 5.6 | 325 | 0.1337 | 0.2381 | 0.1198 | 0.1594 | 0.9704 |
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+ | 0.1235 | 6.03 | 350 | 0.1215 | 0.0 | 0.0 | 0.0 | 0.9705 |
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+ | 0.1165 | 6.47 | 375 | 0.1337 | 0.3613 | 0.1677 | 0.2290 | 0.9739 |
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+ | 0.1184 | 6.9 | 400 | 0.1228 | 0.2303 | 0.1228 | 0.1602 | 0.9718 |
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+ | 0.1076 | 7.33 | 425 | 0.1174 | 0.2646 | 0.3263 | 0.2922 | 0.9671 |
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+ | 0.0964 | 7.76 | 450 | 0.1094 | 0.3972 | 0.2545 | 0.3102 | 0.9751 |
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+ | 0.0902 | 8.19 | 475 | 0.1217 | 0.4264 | 0.2515 | 0.3164 | 0.9742 |
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+ | 0.0891 | 8.62 | 500 | 0.1075 | 0.3746 | 0.3263 | 0.3488 | 0.9736 |
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+ | 0.0813 | 9.05 | 525 | 0.1295 | 0.4354 | 0.2725 | 0.3352 | 0.9738 |
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+ | 0.078 | 9.48 | 550 | 0.1067 | 0.375 | 0.3413 | 0.3574 | 0.9742 |
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+ | 0.0751 | 9.91 | 575 | 0.1042 | 0.4905 | 0.3084 | 0.3787 | 0.9765 |
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+ | 0.0683 | 10.34 | 600 | 0.1028 | 0.4672 | 0.3413 | 0.3945 | 0.9761 |
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+ | 0.0687 | 10.78 | 625 | 0.1070 | 0.4975 | 0.2994 | 0.3738 | 0.9762 |
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+ | 0.0664 | 11.21 | 650 | 0.1225 | 0.3256 | 0.3383 | 0.3319 | 0.9703 |
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+ | 0.0565 | 11.64 | 675 | 0.1000 | 0.4487 | 0.3144 | 0.3697 | 0.9767 |
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+ | 0.0555 | 12.07 | 700 | 0.1033 | 0.4463 | 0.3234 | 0.375 | 0.9757 |
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+ | 0.045 | 12.5 | 725 | 0.1150 | 0.4237 | 0.3323 | 0.3725 | 0.9746 |
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+ | 0.0514 | 12.93 | 750 | 0.1126 | 0.6 | 0.3503 | 0.4423 | 0.9774 |
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+ | 0.0387 | 13.36 | 775 | 0.1409 | 0.3986 | 0.3473 | 0.3712 | 0.9742 |
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+ | 0.0419 | 13.79 | 800 | 0.1096 | 0.4336 | 0.4401 | 0.4368 | 0.9723 |
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+ | 0.0349 | 14.22 | 825 | 0.1207 | 0.4902 | 0.3743 | 0.4244 | 0.9769 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.27.4
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+ - Pytorch 2.0.0+cu118
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+ - Datasets 2.11.0
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+ - Tokenizers 0.13.2