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Vishveshwara/NER-Contract

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README.md ADDED
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+ ---
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+ license: mit
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ base_model: roberta-large
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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: bert-large-token-classification
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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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+ # bert-large-token-classification
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+
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+ This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2157
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+ - Precision: 0.4271
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+ - Recall: 0.5155
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+ - F1: 0.4671
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+ - Accuracy: 0.9481
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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: 0.001
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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: 5
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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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+ | 0.3642 | 1.0 | 741 | 0.2888 | 0.2211 | 0.2315 | 0.2262 | 0.9264 |
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+ | 0.2508 | 2.0 | 1482 | 0.2862 | 0.3301 | 0.3645 | 0.3465 | 0.9217 |
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+ | 0.1609 | 3.0 | 2223 | 0.2247 | 0.3109 | 0.4309 | 0.3612 | 0.9411 |
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+ | 0.1404 | 4.0 | 2964 | 0.2391 | 0.3563 | 0.4669 | 0.4042 | 0.9303 |
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+ | 0.0937 | 5.0 | 3705 | 0.2157 | 0.4271 | 0.5155 | 0.4671 | 0.9481 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.41.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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