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End of training

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README.md ADDED
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+ ---
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+ base_model: vinai/bertweet-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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: bertweet-base_3epoch10
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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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+ # bertweet-base_3epoch10
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+
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+ This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.7005
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+ - Accuracy: 0.7392
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+ - F1: 0.4217
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+ - Precision: 0.5789
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+ - Recall: 0.3317
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+ - Precision Sarcastic: 0.5789
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+ - Recall Sarcastic: 0.3317
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+ - F1 Sarcastic: 0.4217
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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: 16
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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 | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
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+ | No log | 1.0 | 174 | 1.3971 | 0.7493 | 0.4 | 0.6374 | 0.2915 | 0.6374 | 0.2915 | 0.4 |
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+ | No log | 2.0 | 348 | 1.0371 | 0.7334 | 0.3854 | 0.5686 | 0.2915 | 0.5686 | 0.2915 | 0.3854 |
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+ | 0.0617 | 3.0 | 522 | 1.6060 | 0.7147 | 0.4277 | 0.5034 | 0.3719 | 0.5034 | 0.3719 | 0.4277 |
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+ | 0.0617 | 4.0 | 696 | 1.3603 | 0.7464 | 0.4172 | 0.6117 | 0.3166 | 0.6117 | 0.3166 | 0.4172 |
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+ | 0.0617 | 5.0 | 870 | 1.5872 | 0.7478 | 0.4373 | 0.6071 | 0.3417 | 0.6071 | 0.3417 | 0.4373 |
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+ | 0.032 | 6.0 | 1044 | 1.4206 | 0.7493 | 0.3916 | 0.6437 | 0.2814 | 0.6437 | 0.2814 | 0.3916 |
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+ | 0.032 | 7.0 | 1218 | 1.4775 | 0.7507 | 0.4055 | 0.6413 | 0.2965 | 0.6413 | 0.2965 | 0.4055 |
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+ | 0.032 | 8.0 | 1392 | 1.5835 | 0.7421 | 0.4389 | 0.5833 | 0.3518 | 0.5833 | 0.3518 | 0.4389 |
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+ | 0.0125 | 9.0 | 1566 | 1.7009 | 0.7464 | 0.3846 | 0.6322 | 0.2764 | 0.6322 | 0.2764 | 0.3846 |
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+ | 0.0125 | 10.0 | 1740 | 1.7005 | 0.7392 | 0.4217 | 0.5789 | 0.3317 | 0.5789 | 0.3317 | 0.4217 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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