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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/bert-fa-base-uncased |
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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: Bert-Sentiment-Fa |
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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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# Bert-Sentiment-Fa |
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This model is a fine-tuned version of [HooshvareLab/bert-fa-base-uncased](https://huggingface.co/HooshvareLab/bert-fa-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1484 |
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- Accuracy: 0.8417 |
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- F1: 0.8524 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 64 |
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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: 15 |
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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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| No log | 1.0 | 68 | 0.5099 | 0.8042 | 0.8062 | |
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| No log | 2.0 | 136 | 0.6354 | 0.8083 | 0.8079 | |
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| No log | 3.0 | 204 | 0.6376 | 0.8458 | 0.8575 | |
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| No log | 4.0 | 272 | 0.8837 | 0.8292 | 0.8373 | |
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| No log | 5.0 | 340 | 0.9432 | 0.8167 | 0.8335 | |
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| No log | 6.0 | 408 | 0.9680 | 0.8125 | 0.8128 | |
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| No log | 7.0 | 476 | 0.8569 | 0.8292 | 0.8402 | |
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| 0.1247 | 8.0 | 544 | 1.0439 | 0.8542 | 0.8628 | |
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| 0.1247 | 9.0 | 612 | 1.0181 | 0.8375 | 0.8451 | |
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| 0.1247 | 10.0 | 680 | 1.0169 | 0.8458 | 0.8556 | |
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| 0.1247 | 11.0 | 748 | 1.1128 | 0.8292 | 0.8348 | |
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| 0.1247 | 12.0 | 816 | 1.1325 | 0.8333 | 0.8382 | |
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| 0.1247 | 13.0 | 884 | 1.1458 | 0.85 | 0.8622 | |
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| 0.1247 | 14.0 | 952 | 1.1439 | 0.85 | 0.8622 | |
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| 0.0062 | 15.0 | 1020 | 1.1484 | 0.8417 | 0.8524 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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