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End of training

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  1. README.md +67 -0
  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ base_model: allenai/scibert_scivocab_uncased
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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: SciBERT_CRAFT_NER_new
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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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+ # SciBERT_CRAFT_NER_new
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+
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+ This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1199
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+ - Precision: 0.9743
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+ - Recall: 0.9761
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+ - F1: 0.9752
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+ - Accuracy: 0.9740
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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: 3
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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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+ | 0.1537 | 1.0 | 695 | 0.1140 | 0.9707 | 0.9727 | 0.9717 | 0.9704 |
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+ | 0.0452 | 2.0 | 1390 | 0.1128 | 0.9733 | 0.9750 | 0.9741 | 0.9731 |
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+ | 0.0185 | 3.0 | 2085 | 0.1199 | 0.9743 | 0.9761 | 0.9752 | 0.9740 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.0
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+ - Tokenizers 0.15.0
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