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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: google/flan-t5-large |
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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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- precision |
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- recall |
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model-index: |
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- name: flanT5_Task1 |
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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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# flanT5_Task1 |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6498 |
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- Accuracy: 0.8047 |
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- Precision: 0.8229 |
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- Recall: 0.7765 |
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- F1 score: 0.7990 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 score | Precision | Recall | Validation Loss | |
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|:-------------:|:------:|:-----:|:--------:|:--------:|:---------:|:------:|:---------------:| |
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| 1.0024 | 0.4205 | 2500 | 0.76 | 0.7530 | 0.7756 | 0.7318 | 0.8479 | |
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| 1.0808 | 0.8410 | 5000 | 0.7553 | 0.7620 | 0.7416 | 0.7835 | 0.8954 | |
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| 1.0927 | 1.2616 | 7500 | 0.7682 | 0.7411 | 0.8393 | 0.6635 | 1.0011 | |
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| 0.8823 | 1.6821 | 10000 | 0.7847 | 0.7738 | 0.8151 | 0.7365 | 0.8913 | |
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| 0.8154 | 2.1026 | 12500 | 0.7929 | 0.7822 | 0.8251 | 0.7435 | 0.8291 | |
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| 0.6981 | 2.5231 | 15000 | 0.9793 | 0.7929 | 0.8152 | 0.7576 | 0.7854 | |
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| 0.6452 | 2.9437 | 17500 | 0.9164 | 0.8035 | 0.8564 | 0.7294 | 0.7878 | |
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| 0.4567 | 3.3642 | 20000 | 1.0961 | 0.8153 | 0.8418 | 0.7765 | 0.8078 | |
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| 0.4245 | 3.7847 | 22500 | 1.2257 | 0.8153 | 0.8268 | 0.7976 | 0.8120 | |
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| 0.3159 | 4.2052 | 25000 | 1.4984 | 0.8047 | 0.8047 | 0.8047 | 0.8047 | |
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| 0.2152 | 4.6257 | 27500 | 1.6498 | 0.8047 | 0.8229 | 0.7765 | 0.7990 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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