arnabdhar commited on
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End of training

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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ license: mit
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+ base_model: roberta-base
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+ tags:
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+ - pytorch
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+ - RobertaForTokenClassification
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+ - named-entity-recognition
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+ - roberta-base
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+ - generated_from_trainer
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+ metrics:
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+ - recall
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+ - precision
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: roberta-base-ontonotes
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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-base-ontonotes
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the tner/ontonotes5 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0695
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+ - Recall: 0.9227
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+ - Precision: 0.9013
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+ - F1: 0.9118
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+ - Accuracy: 0.9820
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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: 8e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 160
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+ - seed: 75241309
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - training_steps: 6000
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:|
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+ | 0.1305 | 0.31 | 600 | 0.1169 | 0.8550 | 0.8139 | 0.8340 | 0.9681 |
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+ | 0.118 | 0.63 | 1200 | 0.0925 | 0.8769 | 0.8592 | 0.8680 | 0.9750 |
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+ | 0.0937 | 0.94 | 1800 | 0.0874 | 0.8939 | 0.8609 | 0.8771 | 0.9764 |
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+ | 0.0698 | 1.25 | 2400 | 0.0821 | 0.9066 | 0.8775 | 0.8918 | 0.9784 |
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+ | 0.0663 | 1.56 | 3000 | 0.0827 | 0.9124 | 0.8764 | 0.8940 | 0.9789 |
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+ | 0.0624 | 1.88 | 3600 | 0.0732 | 0.9179 | 0.8868 | 0.9021 | 0.9804 |
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+ | 0.0364 | 2.19 | 4200 | 0.0750 | 0.9204 | 0.8968 | 0.9085 | 0.9816 |
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+ | 0.0429 | 2.5 | 4800 | 0.0699 | 0.9198 | 0.9031 | 0.9114 | 0.9818 |
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+ | 0.0323 | 2.82 | 5400 | 0.0697 | 0.9227 | 0.9008 | 0.9116 | 0.9819 |
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+ | 0.0334 | 3.13 | 6000 | 0.0695 | 0.9227 | 0.9013 | 0.9118 | 0.9820 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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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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+ "architectures": [
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+ "RobertaForTokenClassification"
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+ ],
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+ "20": "B-FAC",
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+ "23": "B-LOC",
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "roberta",
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+ "pad_token_id": 1,
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