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Shijia
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run1

Text2Text Generation
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text-generation-inference
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README.md ADDED
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+ ---
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+ base_model: medicalai/ClinicalBERT
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - sem_eval_2024_task_2
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: run1
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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: sem_eval_2024_task_2
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+ type: sem_eval_2024_task_2
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+ config: sem_eval_2024_task_2_source
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+ split: validation
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+ args: sem_eval_2024_task_2_source
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.595
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+ - name: Precision
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+ type: precision
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+ value: 0.632109581421221
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+ - name: Recall
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+ type: recall
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+ value: 0.595
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+ - name: F1
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+ type: f1
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+ value: 0.5644107445349681
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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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+ # run1
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+
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+ This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on the sem_eval_2024_task_2 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6989
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+ - Accuracy: 0.595
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+ - Precision: 0.6321
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+ - Recall: 0.595
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+ - F1: 0.5644
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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: 64
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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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: 20
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+ - mixed_precision_training: Native AMP
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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 | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 0.99 | 53 | 0.6932 | 0.5 | 0.5 | 0.5 | 0.4302 |
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+ | 0.6952 | 2.0 | 107 | 0.6946 | 0.505 | 0.5059 | 0.505 | 0.4854 |
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+ | 0.6952 | 2.99 | 160 | 0.6938 | 0.485 | 0.4127 | 0.485 | 0.3505 |
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+ | 0.6953 | 4.0 | 214 | 0.6937 | 0.5 | 0.5 | 0.5 | 0.4389 |
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+ | 0.6953 | 4.99 | 267 | 0.6961 | 0.5 | 0.25 | 0.5 | 0.3333 |
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+ | 0.6937 | 6.0 | 321 | 0.6936 | 0.5 | 0.25 | 0.5 | 0.3333 |
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+ | 0.6937 | 6.99 | 374 | 0.6908 | 0.495 | 0.4487 | 0.495 | 0.3479 |
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+ | 0.6927 | 8.0 | 428 | 0.6804 | 0.545 | 0.5485 | 0.545 | 0.5366 |
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+ | 0.6927 | 8.99 | 481 | 0.6888 | 0.525 | 0.5535 | 0.525 | 0.4520 |
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+ | 0.6799 | 10.0 | 535 | 0.6657 | 0.615 | 0.6476 | 0.615 | 0.5925 |
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+ | 0.6799 | 10.99 | 588 | 0.6600 | 0.625 | 0.6448 | 0.625 | 0.6117 |
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+ | 0.6509 | 12.0 | 642 | 0.6598 | 0.595 | 0.6407 | 0.595 | 0.5592 |
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+ | 0.6509 | 12.99 | 695 | 0.6598 | 0.605 | 0.6555 | 0.605 | 0.5701 |
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+ | 0.6122 | 14.0 | 749 | 0.6643 | 0.59 | 0.6234 | 0.59 | 0.5603 |
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+ | 0.6122 | 14.99 | 802 | 0.6754 | 0.605 | 0.6818 | 0.605 | 0.5584 |
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+ | 0.5601 | 16.0 | 856 | 0.6788 | 0.605 | 0.6382 | 0.605 | 0.5798 |
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+ | 0.5601 | 16.99 | 909 | 0.6864 | 0.59 | 0.6234 | 0.59 | 0.5603 |
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+ | 0.5159 | 18.0 | 963 | 0.6967 | 0.6 | 0.6457 | 0.6 | 0.5660 |
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+ | 0.5159 | 18.99 | 1016 | 0.7037 | 0.6 | 0.6507 | 0.6 | 0.5633 |
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+ | 0.5117 | 19.81 | 1060 | 0.6989 | 0.595 | 0.6321 | 0.595 | 0.5644 |
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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 2.15.0
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+ - Tokenizers 0.15.0
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