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--- |
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license: apache-2.0 |
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base_model: HooshvareLab/roberta-fa-zwnj-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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- f1 |
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- precision |
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model-index: |
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- name: roberta-fa-zwnj-base_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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# roberta-fa-zwnj-base_v1 |
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This model is a fine-tuned version of [HooshvareLab/roberta-fa-zwnj-base](https://huggingface.co/HooshvareLab/roberta-fa-zwnj-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3797 |
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- Accuracy: 0.6288 |
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- F1: 0.6282 |
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- Precision: 0.6299 |
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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: 1e-05 |
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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 | 1.1404 | 0.5176 | 0.4956 | 0.5475 | |
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| No log | 2.0 | 442 | 0.9659 | 0.6163 | 0.6136 | 0.6169 | |
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| 1.0628 | 3.0 | 663 | 0.9516 | 0.6436 | 0.6405 | 0.6456 | |
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| 1.0628 | 4.0 | 884 | 0.9857 | 0.6470 | 0.6462 | 0.6530 | |
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| 0.6388 | 5.0 | 1105 | 1.0326 | 0.6481 | 0.6483 | 0.6490 | |
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| 0.6388 | 6.0 | 1326 | 1.1403 | 0.6652 | 0.6647 | 0.6664 | |
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| 0.3767 | 7.0 | 1547 | 1.2419 | 0.6356 | 0.6362 | 0.6383 | |
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| 0.3767 | 8.0 | 1768 | 1.3099 | 0.6402 | 0.6394 | 0.6398 | |
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| 0.3767 | 9.0 | 1989 | 1.3632 | 0.6300 | 0.6298 | 0.6297 | |
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| 0.2179 | 10.0 | 2210 | 1.3797 | 0.6288 | 0.6282 | 0.6299 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.2 |
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