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license: apache-2.0 |
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base_model: HooshvareLab/bert-fa-base-uncased-clf-persiannews |
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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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model-index: |
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- name: uncased-clf-persiannews_v1 |
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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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# uncased-clf-persiannews_v1 |
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This model is a fine-tuned version of [HooshvareLab/bert-fa-base-uncased-clf-persiannews](https://huggingface.co./HooshvareLab/bert-fa-base-uncased-clf-persiannews) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4385 |
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- Accuracy: 0.6459 |
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- F1: 0.6461 |
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- Precision: 0.6470 |
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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-06 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:| |
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| No log | 1.0 | 221 | 1.0855 | 0.6277 | 0.6263 | 0.6472 | |
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| No log | 2.0 | 442 | 1.0924 | 0.6549 | 0.6545 | 0.6598 | |
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| 0.4554 | 3.0 | 663 | 1.1278 | 0.6583 | 0.6570 | 0.6609 | |
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| 0.4554 | 4.0 | 884 | 1.2085 | 0.6481 | 0.6488 | 0.6559 | |
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| 0.2653 | 5.0 | 1105 | 1.2614 | 0.6481 | 0.6487 | 0.6498 | |
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| 0.2653 | 6.0 | 1326 | 1.3392 | 0.6402 | 0.6371 | 0.6433 | |
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| 0.1817 | 7.0 | 1547 | 1.3692 | 0.6549 | 0.6543 | 0.6572 | |
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| 0.1817 | 8.0 | 1768 | 1.4216 | 0.6425 | 0.6419 | 0.6424 | |
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| 0.1817 | 9.0 | 1989 | 1.4325 | 0.6549 | 0.6551 | 0.6555 | |
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| 0.1334 | 10.0 | 2210 | 1.4385 | 0.6459 | 0.6461 | 0.6470 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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