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--- |
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base_model: google/flan-t5-base |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: results |
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results: [] |
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pipeline_tag: text-generation |
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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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# results |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co./google/flan-t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6519 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 12 |
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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: 16 |
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- training_steps: 1698 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.2568 | 0.59 | 50 | 2.9764 | |
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| 3.2186 | 1.18 | 100 | 2.9349 | |
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| 3.1884 | 1.76 | 150 | 2.8820 | |
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| 3.1448 | 2.35 | 200 | 2.8404 | |
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| 3.1166 | 2.94 | 250 | 2.8120 | |
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| 3.0742 | 3.53 | 300 | 2.7899 | |
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| 3.0662 | 4.12 | 350 | 2.7724 | |
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| 3.0379 | 4.71 | 400 | 2.7578 | |
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| 3.0301 | 5.29 | 450 | 2.7457 | |
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| 3.0071 | 5.88 | 500 | 2.7352 | |
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| 3.0084 | 6.47 | 550 | 2.7259 | |
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| 2.9632 | 7.06 | 600 | 2.7177 | |
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| 2.9706 | 7.65 | 650 | 2.7104 | |
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| 2.9543 | 8.24 | 700 | 2.7037 | |
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| 2.9573 | 8.82 | 750 | 2.6979 | |
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| 2.9663 | 9.41 | 800 | 2.6928 | |
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| 2.9243 | 10.0 | 850 | 2.6877 | |
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| 2.9451 | 10.59 | 900 | 2.6832 | |
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| 2.9027 | 11.18 | 950 | 2.6790 | |
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| 2.9255 | 11.76 | 1000 | 2.6754 | |
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| 2.916 | 12.35 | 1050 | 2.6719 | |
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| 2.9155 | 12.94 | 1100 | 2.6688 | |
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| 2.9223 | 13.53 | 1150 | 2.6659 | |
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| 2.9141 | 14.12 | 1200 | 2.6635 | |
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| 2.8931 | 14.71 | 1250 | 2.6612 | |
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| 2.8988 | 15.29 | 1300 | 2.6590 | |
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| 2.8986 | 15.88 | 1350 | 2.6573 | |
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| 2.8998 | 16.47 | 1400 | 2.6558 | |
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| 2.9004 | 17.06 | 1450 | 2.6546 | |
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| 2.9036 | 17.65 | 1500 | 2.6535 | |
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| 2.885 | 18.24 | 1550 | 2.6528 | |
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| 2.8994 | 18.82 | 1600 | 2.6522 | |
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| 2.8971 | 19.41 | 1650 | 2.6519 | |
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### Framework versions |
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- PEFT 0.8.2 |
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- Transformers 4.38.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
