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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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<!-- 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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# bertweetB_15epoch |
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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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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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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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### Framework versions |
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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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