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roberta-es-clinical-trials-ner-fd-text_cl

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: cc-by-nc-4.0
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+ base_model: lcampillos/roberta-es-clinical-trials-ner
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - recall
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+ - precision
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+ - f1
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+ model-index:
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+ - name: roberta-es-clinical-trials-ner-fd-text_cl
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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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+ # roberta-es-clinical-trials-ner-fd-text_cl
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+
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+ This model is a fine-tuned version of [lcampillos/roberta-es-clinical-trials-ner](https://huggingface.co/lcampillos/roberta-es-clinical-trials-ner) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0955
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+ - Accuracy: 0.8961
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+ - Recall: 0.9353
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+ - Precision: 0.8926
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+ - F1: 0.9134
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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: Use OptimizerNames.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 | Accuracy | Recall | Precision | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 231 | 0.2599 | 0.9107 | 0.9273 | 0.9209 | 0.9241 |
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+ | No log | 2.0 | 462 | 0.4050 | 0.9008 | 0.9482 | 0.8897 | 0.9180 |
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+ | 0.1696 | 3.0 | 693 | 0.5082 | 0.8944 | 0.9412 | 0.8857 | 0.9126 |
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+ | 0.1696 | 4.0 | 924 | 0.7025 | 0.8821 | 0.9323 | 0.8748 | 0.9026 |
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+ | 0.0363 | 5.0 | 1155 | 0.6880 | 0.9026 | 0.9432 | 0.8959 | 0.9190 |
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+ | 0.0363 | 6.0 | 1386 | 0.6909 | 0.9096 | 0.9263 | 0.9199 | 0.9231 |
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+ | 0.0051 | 7.0 | 1617 | 0.8435 | 0.8938 | 0.9462 | 0.8813 | 0.9126 |
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+ | 0.0051 | 8.0 | 1848 | 0.9259 | 0.8891 | 0.9452 | 0.8755 | 0.9090 |
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+ | 0.0085 | 9.0 | 2079 | 0.7661 | 0.9043 | 0.9253 | 0.9126 | 0.9189 |
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+ | 0.0085 | 10.0 | 2310 | 0.8466 | 0.8915 | 0.9452 | 0.8787 | 0.9107 |
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+ | 0.0063 | 11.0 | 2541 | 0.8288 | 0.9043 | 0.9183 | 0.9183 | 0.9183 |
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+ | 0.0063 | 12.0 | 2772 | 0.9942 | 0.8827 | 0.9472 | 0.8653 | 0.9044 |
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+ | 0.009 | 13.0 | 3003 | 0.5731 | 0.9294 | 0.9223 | 0.9556 | 0.9387 |
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+ | 0.009 | 14.0 | 3234 | 0.7689 | 0.9084 | 0.9402 | 0.9068 | 0.9232 |
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+ | 0.009 | 15.0 | 3465 | 1.2144 | 0.8687 | 0.9532 | 0.8432 | 0.8948 |
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+ | 0.0017 | 16.0 | 3696 | 0.9313 | 0.8956 | 0.9283 | 0.8970 | 0.9124 |
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+ | 0.0017 | 17.0 | 3927 | 0.8994 | 0.9049 | 0.9213 | 0.9167 | 0.9190 |
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+ | 0.001 | 18.0 | 4158 | 0.9995 | 0.8956 | 0.9323 | 0.8940 | 0.9127 |
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+ | 0.001 | 19.0 | 4389 | 1.0237 | 0.8932 | 0.9333 | 0.8898 | 0.9110 |
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+ | 0.0007 | 20.0 | 4620 | 1.0355 | 0.8938 | 0.9373 | 0.8877 | 0.9118 |
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+ | 0.0007 | 21.0 | 4851 | 1.0372 | 0.8944 | 0.9343 | 0.8908 | 0.9120 |
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+ | 0.0006 | 22.0 | 5082 | 1.0451 | 0.8944 | 0.9343 | 0.8908 | 0.9120 |
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+ | 0.0006 | 23.0 | 5313 | 1.0461 | 0.8944 | 0.9343 | 0.8908 | 0.9120 |
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+ | 0.0004 | 24.0 | 5544 | 1.0582 | 0.8932 | 0.9343 | 0.8891 | 0.9111 |
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+ | 0.0004 | 25.0 | 5775 | 1.0680 | 0.8944 | 0.9373 | 0.8886 | 0.9123 |
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+ | 0.0008 | 26.0 | 6006 | 1.0828 | 0.8921 | 0.9343 | 0.8874 | 0.9102 |
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+ | 0.0008 | 27.0 | 6237 | 1.0875 | 0.8932 | 0.9442 | 0.8819 | 0.9120 |
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+ | 0.0008 | 28.0 | 6468 | 1.0394 | 0.8961 | 0.9223 | 0.9025 | 0.9123 |
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+ | 0.0022 | 29.0 | 6699 | 1.0938 | 0.8961 | 0.9353 | 0.8926 | 0.9134 |
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+ | 0.0022 | 30.0 | 6930 | 1.0955 | 0.8961 | 0.9353 | 0.8926 | 0.9134 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.51.3
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.5.0
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+ - Tokenizers 0.21.1
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