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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: flan-t5-small-qclassifier_new_0.6-droprob_0.2-smooth_0.1-lr_1e-5-dcy_0.0001 |
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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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# flan-t5-small-qclassifier_new_0.6-droprob_0.2-smooth_0.1-lr_1e-5-dcy_0.0001 |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5710 |
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- Precision: 0.7404 |
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- Recall: 1.0 |
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- F1: 0.8509 |
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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: 64 |
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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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- label_smoothing_factor: 0.1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| |
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| 0.6235 | 1.0 | 193 | 0.5839 | 0.7395 | 1.0 | 0.8502 | |
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| 0.5853 | 2.0 | 386 | 0.5768 | 0.7395 | 1.0 | 0.8502 | |
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| 0.5783 | 3.0 | 579 | 0.5741 | 0.7395 | 1.0 | 0.8502 | |
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| 0.5739 | 4.0 | 772 | 0.5745 | 0.7395 | 1.0 | 0.8502 | |
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| 0.5714 | 5.0 | 965 | 0.5711 | 0.7395 | 1.0 | 0.8502 | |
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| 0.5695 | 6.0 | 1158 | 0.5710 | 0.7404 | 1.0 | 0.8509 | |
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| 0.5672 | 7.0 | 1351 | 0.5718 | 0.7404 | 1.0 | 0.8509 | |
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| 0.5639 | 8.0 | 1544 | 0.5715 | 0.7415 | 0.9956 | 0.8500 | |
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| 0.5624 | 9.0 | 1737 | 0.5725 | 0.7416 | 0.9912 | 0.8485 | |
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| 0.5619 | 10.0 | 1930 | 0.5715 | 0.7431 | 0.9860 | 0.8475 | |
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| 0.5613 | 11.0 | 2123 | 0.5720 | 0.7422 | 0.9842 | 0.8463 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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