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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: HooshvareLab/albert-fa-zwnj-base-v2 |
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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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model-index: |
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- name: albert-fa-zwnj-base-v2-finetuned-bmd-20241021-LOSO-section-out1 |
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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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# albert-fa-zwnj-base-v2-finetuned-bmd-20241021-LOSO-section-out1 |
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This model is a fine-tuned version of [HooshvareLab/albert-fa-zwnj-base-v2](https://huggingface.co/HooshvareLab/albert-fa-zwnj-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1964 |
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- Accuracy: 0.3103 |
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- F1: 0.2745 |
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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: 8 |
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- eval_batch_size: 8 |
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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_ratio: 0.1 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.1384 | 1.0 | 14 | 1.2494 | 0.3448 | 0.1768 | |
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| 1.1313 | 2.0 | 28 | 1.0923 | 0.3103 | 0.1724 | |
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| 0.9349 | 3.0 | 42 | 1.2456 | 0.3448 | 0.2468 | |
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| 0.6109 | 4.0 | 56 | 1.3296 | 0.2069 | 0.1970 | |
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| 0.3213 | 5.0 | 70 | 1.4808 | 0.3793 | 0.3711 | |
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| 0.1212 | 6.0 | 84 | 1.9444 | 0.2414 | 0.2352 | |
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| 0.0406 | 7.0 | 98 | 2.6696 | 0.4138 | 0.3814 | |
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| 0.0239 | 8.0 | 112 | 2.6279 | 0.2759 | 0.2705 | |
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| 0.005 | 9.0 | 126 | 3.0941 | 0.3103 | 0.2745 | |
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| 0.0041 | 10.0 | 140 | 3.1964 | 0.3103 | 0.2745 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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