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update model card README.md

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+ ---
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+ base_model: readerbench/RoBERT-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ model-index:
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+ - name: ro-offense-01
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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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+ # ro-offense-01
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+
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+ This model is a fine-tuned version of [readerbench/RoBERT-base](https://huggingface.co/readerbench/RoBERT-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7285
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+ - Accuracy: 0.8132
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+ - Precision: 0.8131
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+ - Recall: 0.8173
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+ - F1 Macro: 0.8123
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+ - F1 Micro: 0.8132
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+ - F1 Weighted: 0.8094
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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: 64
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+ - eval_batch_size: 128
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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: 10
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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 Macro | F1 Micro | F1 Weighted |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:--------:|:-----------:|
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+ | No log | 1.0 | 125 | 0.6284 | 0.7675 | 0.7662 | 0.7721 | 0.7681 | 0.7675 | 0.7654 |
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+ | No log | 2.0 | 250 | 0.5576 | 0.7820 | 0.7826 | 0.7799 | 0.7796 | 0.7820 | 0.7803 |
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+ | No log | 3.0 | 375 | 0.5405 | 0.8001 | 0.8122 | 0.8077 | 0.8026 | 0.8001 | 0.7943 |
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+ | 0.5338 | 4.0 | 500 | 0.5853 | 0.8172 | 0.8140 | 0.8120 | 0.8124 | 0.8172 | 0.8161 |
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+ | 0.5338 | 5.0 | 625 | 0.6476 | 0.8157 | 0.8143 | 0.8098 | 0.8118 | 0.8157 | 0.8148 |
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+ | 0.5338 | 6.0 | 750 | 0.6607 | 0.8122 | 0.8137 | 0.8173 | 0.8120 | 0.8122 | 0.8082 |
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+ | 0.5338 | 7.0 | 875 | 0.7285 | 0.8132 | 0.8131 | 0.8173 | 0.8123 | 0.8132 | 0.8094 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.3
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+ - Tokenizers 0.13.3