| | ---
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| | license: mit
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| | base_model: FacebookAI/roberta-large
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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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| | model-index:
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| | - name: fine_tuned_3e-5
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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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| | # fine_tuned_3e-5
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| |
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| | This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 0.0369
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| | - Accuracy: 0.9933
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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: 3e-05
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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: 3
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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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| | | 0.4112 | 0.15 | 100 | 0.2334 | 0.96 |
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| | | 0.3366 | 0.3 | 200 | 0.2366 | 0.96 |
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| | | 0.2548 | 0.44 | 300 | 0.3344 | 0.9233 |
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| | | 0.1728 | 0.59 | 400 | 0.5630 | 0.9017 |
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| | | 0.1559 | 0.74 | 500 | 0.1761 | 0.9733 |
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| | | 0.1139 | 0.89 | 600 | 0.9891 | 0.835 |
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| | | 0.1084 | 1.04 | 700 | 0.1377 | 0.9733 |
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| | | 0.0551 | 1.19 | 800 | 0.0782 | 0.9833 |
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| | | 0.0829 | 1.33 | 900 | 0.0325 | 0.9933 |
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| | | 0.0411 | 1.48 | 1000 | 0.0369 | 0.9933 |
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| | | 0.0274 | 1.63 | 1100 | 0.0144 | 0.9983 |
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| | | 0.0242 | 1.78 | 1200 | 0.0524 | 0.9933 |
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| | | 0.0261 | 1.93 | 1300 | 0.1679 | 0.9817 |
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| | | 0.0115 | 2.07 | 1400 | 0.0870 | 0.9883 |
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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 2.1.1+cu118
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| | - Datasets 2.16.0
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| | - Tokenizers 0.15.0
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| |
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