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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: skt/A.X-Encoder-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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model-index: |
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- name: aha_sentence_classification |
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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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# aha_sentence_classification |
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This model is a fine-tuned version of [skt/A.X-Encoder-base](https://huggingface.co/skt/A.X-Encoder-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8454 |
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- Accuracy: 0.6900 |
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- F1 Micro: 0.6900 |
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- F1 Macro: 0.6503 |
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- Precision Macro: 0.6078 |
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- Recall Macro: 0.7221 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Micro | F1 Macro | Precision Macro | Recall Macro | |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|:--------:|:--------:|:---------------:|:------------:| |
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| 0.9702 | 0.5949 | 1000 | 1.1520 | 0.5590 | 0.5590 | 0.5444 | 0.5142 | 0.6791 | |
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| 0.7293 | 1.1898 | 2000 | 1.0469 | 0.5992 | 0.5992 | 0.5966 | 0.5599 | 0.7238 | |
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| 0.7779 | 1.7847 | 3000 | 0.9977 | 0.6278 | 0.6278 | 0.5964 | 0.5646 | 0.7274 | |
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| 0.5545 | 2.3795 | 4000 | 0.9847 | 0.6290 | 0.6290 | 0.6208 | 0.5849 | 0.7236 | |
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| 0.5692 | 2.9744 | 5000 | 0.8454 | 0.6900 | 0.6900 | 0.6503 | 0.6078 | 0.7221 | |
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| 0.3962 | 3.5693 | 6000 | 1.0074 | 0.6488 | 0.6488 | 0.6316 | 0.6093 | 0.7081 | |
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| 0.1624 | 4.1642 | 7000 | 1.1059 | 0.6732 | 0.6732 | 0.6533 | 0.6322 | 0.6930 | |
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| 0.1816 | 4.7591 | 8000 | 1.1277 | 0.6872 | 0.6872 | 0.6513 | 0.6429 | 0.6690 | |
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| 0.0934 | 5.3540 | 9000 | 1.4084 | 0.6882 | 0.6882 | 0.6468 | 0.6380 | 0.6649 | |
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| 0.0882 | 5.9488 | 10000 | 1.4941 | 0.6918 | 0.6918 | 0.6450 | 0.6428 | 0.6606 | |
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### Framework versions |
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- Transformers 4.56.1 |
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- Pytorch 2.7.0+cu126 |
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- Tokenizers 0.22.0 |
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