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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_3epoch5
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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_3epoch5
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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: 1.0827
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+ - Accuracy: 0.7464
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+ - F1: 0.4094
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+ - Precision: 0.6162
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+ - Recall: 0.3065
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+ - Precision Sarcastic: 0.6162
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+ - Recall Sarcastic: 0.3065
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+ - F1 Sarcastic: 0.4094
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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: 5e-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: 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 | Accuracy | F1 | Precision | Recall | Precision Sarcastic | Recall Sarcastic | F1 Sarcastic |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------------------:|:----------------:|:------------:|
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+ | No log | 1.0 | 347 | 0.7068 | 0.7147 | 0.01 | 1.0 | 0.0050 | 1.0 | 0.0050 | 0.01 |
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+ | 0.52 | 2.0 | 694 | 0.5626 | 0.7478 | 0.4957 | 0.5811 | 0.4322 | 0.5811 | 0.4322 | 0.4957 |
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+ | 0.3534 | 3.0 | 1041 | 0.8067 | 0.7651 | 0.4475 | 0.6875 | 0.3317 | 0.6875 | 0.3317 | 0.4475 |
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+ | 0.3534 | 4.0 | 1388 | 0.9764 | 0.7378 | 0.4709 | 0.5586 | 0.4070 | 0.5586 | 0.4070 | 0.4709 |
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+ | 0.1664 | 5.0 | 1735 | 1.0827 | 0.7464 | 0.4094 | 0.6162 | 0.3065 | 0.6162 | 0.3065 | 0.4094 |
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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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