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--- |
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license: apache-2.0 |
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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: output |
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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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# output |
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This model is a fine-tuned version of [HooshvareLab/bert-fa-zwnj-base](https://huggingface.co/HooshvareLab/bert-fa-zwnj-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9434 |
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- Accuracy: 0.6684 |
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- F1: 0.6608 |
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- F1 Micro: 0.6684 |
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- F1 Macro: 0.5384 |
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- Precision: 0.6585 |
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- Recall: 0.6684 |
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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: 0.0001 |
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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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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | F1 Micro | F1 Macro | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:--------:|:---------:|:------:| |
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| No log | 1.0 | 96 | 1.1053 | 0.5789 | 0.5598 | 0.5789 | 0.4428 | 0.5993 | 0.5789 | |
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| No log | 2.0 | 192 | 1.1474 | 0.5737 | 0.5831 | 0.5737 | 0.4693 | 0.6383 | 0.5737 | |
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| No log | 3.0 | 288 | 1.0758 | 0.6316 | 0.6016 | 0.6316 | 0.4850 | 0.6356 | 0.6316 | |
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| No log | 4.0 | 384 | 1.2156 | 0.6474 | 0.6454 | 0.6474 | 0.5224 | 0.6489 | 0.6474 | |
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| No log | 5.0 | 480 | 1.5757 | 0.6316 | 0.6276 | 0.6316 | 0.5099 | 0.6293 | 0.6316 | |
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| 0.5922 | 6.0 | 576 | 1.7277 | 0.6579 | 0.6542 | 0.6579 | 0.5338 | 0.6520 | 0.6579 | |
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| 0.5922 | 7.0 | 672 | 1.9130 | 0.6789 | 0.6736 | 0.6789 | 0.5482 | 0.6749 | 0.6789 | |
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| 0.5922 | 8.0 | 768 | 1.9434 | 0.6684 | 0.6608 | 0.6684 | 0.5384 | 0.6585 | 0.6684 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Tokenizers 0.13.3 |
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