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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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- f1 |
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- recall |
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model-index: |
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- name: bertweet-base |
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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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# bertweet-base |
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This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7685 |
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- F1 Macro: 0.8269 |
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- F1: 0.8697 |
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- F1 Neg: 0.7841 |
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- Acc: 0.8375 |
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- Prec: 0.8930 |
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- Recall: 0.8477 |
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- Mcc: 0.6558 |
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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: 2e-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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- distributed_type: multi-GPU |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:| |
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| 0.6468 | 1.0 | 592 | 0.5371 | 0.7329 | 0.8451 | 0.6207 | 0.78 | 0.7692 | 0.9375 | 0.5069 | |
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| 0.454 | 2.0 | 1184 | 0.5912 | 0.7849 | 0.8419 | 0.7279 | 0.8 | 0.852 | 0.8320 | 0.5702 | |
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| 0.4138 | 3.0 | 1776 | 0.6924 | 0.7853 | 0.8685 | 0.7020 | 0.8175 | 0.8060 | 0.9414 | 0.5951 | |
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| 0.3396 | 4.0 | 2368 | 0.7403 | 0.8233 | 0.8577 | 0.7888 | 0.83 | 0.9234 | 0.8008 | 0.6594 | |
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| 0.3215 | 5.0 | 2960 | 0.7685 | 0.8269 | 0.8697 | 0.7841 | 0.8375 | 0.8930 | 0.8477 | 0.6558 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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