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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: bertweetB_15epoch
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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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+ # bertweetB_15epoch
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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: 0.1645
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+ - Accuracy: 0.77
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+ - Precision: 0.2476
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+ - Recall: 0.3173
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+ - F1: 0.2757
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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: 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: 15
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 1.0 | 217 | 0.1306 | 0.8571 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 434 | 0.1295 | 0.8571 | 0.0 | 0.0 | 0.0 |
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+ | 0.1937 | 3.0 | 651 | 0.1268 | 0.8571 | 0.0 | 0.0 | 0.0 |
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+ | 0.1937 | 4.0 | 868 | 0.1227 | 0.8593 | 0.3712 | 0.0701 | 0.1179 |
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+ | 0.1473 | 5.0 | 1085 | 0.1307 | 0.765 | 0.2292 | 0.4354 | 0.3003 |
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+ | 0.1473 | 6.0 | 1302 | 0.1270 | 0.7964 | 0.2457 | 0.3469 | 0.2877 |
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+ | 0.1018 | 7.0 | 1519 | 0.1398 | 0.7607 | 0.2276 | 0.4354 | 0.2978 |
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+ | 0.1018 | 8.0 | 1736 | 0.1449 | 0.7821 | 0.2323 | 0.3506 | 0.2786 |
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+ | 0.1018 | 9.0 | 1953 | 0.1408 | 0.7843 | 0.2681 | 0.3764 | 0.3127 |
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+ | 0.0648 | 10.0 | 2170 | 0.1535 | 0.78 | 0.2455 | 0.2878 | 0.2634 |
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+ | 0.0648 | 11.0 | 2387 | 0.1585 | 0.7593 | 0.2375 | 0.3911 | 0.2954 |
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+ | 0.0396 | 12.0 | 2604 | 0.1591 | 0.7757 | 0.2642 | 0.3100 | 0.2809 |
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+ | 0.0396 | 13.0 | 2821 | 0.1670 | 0.7614 | 0.2347 | 0.3432 | 0.2774 |
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+ | 0.0284 | 14.0 | 3038 | 0.1623 | 0.7793 | 0.2561 | 0.3026 | 0.2745 |
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+ | 0.0284 | 15.0 | 3255 | 0.1645 | 0.77 | 0.2476 | 0.3173 | 0.2757 |
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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 2.19.2
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+ - Tokenizers 0.19.1
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