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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: michiyasunaga/BioLinkBERT-large
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - scicite
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: cite_classification_model
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: scicite
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+ type: scicite
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+ config: default
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+ split: validation
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.925764192139738
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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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+ # cite_classification_model
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+
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+ This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-large](https://huggingface.co/michiyasunaga/BioLinkBERT-large) on the scicite dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4804
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+ - Accuracy: 0.9258
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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: 8
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.2679 | 1.0 | 513 | 0.1976 | 0.9258 |
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+ | 0.1903 | 2.0 | 1026 | 0.2146 | 0.9225 |
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+ | 0.1474 | 3.0 | 1539 | 0.2356 | 0.9225 |
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+ | 0.1105 | 4.0 | 2052 | 0.3363 | 0.9279 |
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+ | 0.0785 | 5.0 | 2565 | 0.3935 | 0.9225 |
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+ | 0.0498 | 6.0 | 3078 | 0.4296 | 0.9236 |
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+ | 0.0293 | 7.0 | 3591 | 0.4774 | 0.9203 |
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+ | 0.0186 | 8.0 | 4104 | 0.4804 | 0.9258 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.0
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