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--- |
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license: apache-2.0 |
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base_model: google-t5/t5-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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model-index: |
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- name: t5_es_farshad_half_2_4 |
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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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# t5_es_farshad_half_2_4 |
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This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0456 |
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- Accuracy: 0.9916 |
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- F1: 0.9919 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 64 |
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- total_train_batch_size: 4096 |
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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: 1000 |
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- num_epochs: 100 |
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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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| 0.8073 | 5.8501 | 50 | 0.7215 | 0.4858 | 0.0155 | |
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| 0.659 | 11.7002 | 100 | 0.5497 | 0.8353 | 0.8282 | |
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| 0.3485 | 17.5503 | 150 | 0.1162 | 0.9684 | 0.9692 | |
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| 0.0936 | 23.4004 | 200 | 0.0599 | 0.9814 | 0.9821 | |
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| 0.0492 | 29.2505 | 250 | 0.0447 | 0.9875 | 0.9880 | |
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| 0.0316 | 35.1005 | 300 | 0.0426 | 0.9898 | 0.9902 | |
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| 0.0215 | 40.9506 | 350 | 0.0411 | 0.9890 | 0.9894 | |
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| 0.0158 | 46.8007 | 400 | 0.0438 | 0.9907 | 0.9911 | |
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| 0.0131 | 52.6508 | 450 | 0.0389 | 0.9913 | 0.9916 | |
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| 0.0108 | 58.5009 | 500 | 0.0352 | 0.9927 | 0.9930 | |
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| 0.0092 | 64.3510 | 550 | 0.0376 | 0.9922 | 0.9924 | |
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| 0.0075 | 70.2011 | 600 | 0.0416 | 0.9916 | 0.9919 | |
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| 0.0063 | 76.0512 | 650 | 0.0403 | 0.9927 | 0.9930 | |
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| 0.0052 | 81.9013 | 700 | 0.0426 | 0.9925 | 0.9927 | |
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| 0.0045 | 87.7514 | 750 | 0.0443 | 0.9919 | 0.9922 | |
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| 0.0035 | 93.6015 | 800 | 0.0456 | 0.9916 | 0.9919 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.19.1 |
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