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finetuned_BioClinicalBERT

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
text-embeddings-inference
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: emilyalsentzer/Bio_ClinicalBERT
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: finetuned_BioClinicalBERT
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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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+ # finetuned_BioClinicalBERT
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+
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+ This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4147
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+ - F1: 0.9143
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.5879 | 1.0 | 24 | 0.4997 | 0.8767 |
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+ | 0.52 | 2.0 | 48 | 0.4386 | 0.8889 |
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+ | 0.3865 | 3.0 | 72 | 0.4487 | 0.7797 |
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+ | 0.4456 | 4.0 | 96 | 0.5242 | 0.8 |
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+ | 0.2789 | 5.0 | 120 | 0.4147 | 0.9143 |
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+ | 0.2035 | 6.0 | 144 | 0.5301 | 0.8710 |
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+ | 0.124 | 7.0 | 168 | 0.6356 | 0.8923 |
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+ | 0.1422 | 8.0 | 192 | 0.9593 | 0.8308 |
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+ | 0.123 | 9.0 | 216 | 2.0378 | 0.5833 |
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+ | 0.0296 | 10.0 | 240 | 1.1534 | 0.8197 |
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+ | 0.0047 | 11.0 | 264 | 0.6878 | 0.9254 |
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+ | 0.0739 | 12.0 | 288 | 1.2483 | 0.8387 |
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+ | 0.0016 | 13.0 | 312 | 1.9790 | 0.7143 |
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+ | 0.0017 | 14.0 | 336 | 0.9967 | 0.8615 |
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+ | 0.0015 | 15.0 | 360 | 2.0558 | 0.7143 |
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+ | 0.0008 | 16.0 | 384 | 1.2408 | 0.8696 |
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+ | 0.0006 | 17.0 | 408 | 1.6653 | 0.8 |
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+ | 0.0003 | 18.0 | 432 | 1.1586 | 0.875 |
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+ | 0.0002 | 19.0 | 456 | 1.1180 | 0.8955 |
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+ | 0.0002 | 20.0 | 480 | 1.1362 | 0.8955 |
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+ | 0.0002 | 21.0 | 504 | 1.1670 | 0.8955 |
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+ | 0.0002 | 22.0 | 528 | 1.1915 | 0.8955 |
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+ | 0.0002 | 23.0 | 552 | 1.2127 | 0.8955 |
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+ | 0.0002 | 24.0 | 576 | 1.2162 | 0.8955 |
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+ | 0.0002 | 25.0 | 600 | 1.2291 | 0.8955 |
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+ | 0.0002 | 26.0 | 624 | 1.2454 | 0.8955 |
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+ | 0.0002 | 27.0 | 648 | 1.2608 | 0.8955 |
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+ | 0.0002 | 28.0 | 672 | 1.2348 | 0.8923 |
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+ | 0.0002 | 29.0 | 696 | 1.2444 | 0.8923 |
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+ | 0.0001 | 30.0 | 720 | 1.2437 | 0.8923 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.0
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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