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--- |
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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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model-index: |
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- name: models |
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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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# models |
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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: 0.1902 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 0.3389 | 0.0699 | 500 | 0.2668 | |
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| 0.2719 | 0.1398 | 1000 | 0.2524 | |
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| 0.2612 | 0.2097 | 1500 | 0.2381 | |
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| 0.2634 | 0.2796 | 2000 | 0.2313 | |
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| 0.2403 | 0.3495 | 2500 | 0.2260 | |
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| 0.2433 | 0.4193 | 3000 | 0.2190 | |
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| 0.2351 | 0.4892 | 3500 | 0.2168 | |
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| 0.2424 | 0.5591 | 4000 | 0.2109 | |
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| 0.2198 | 0.6290 | 4500 | 0.2071 | |
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| 0.2313 | 0.6989 | 5000 | 0.2062 | |
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| 0.226 | 0.7688 | 5500 | 0.2058 | |
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| 0.2195 | 0.8387 | 6000 | 0.2030 | |
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| 0.2173 | 0.9086 | 6500 | 0.2009 | |
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| 0.2359 | 0.9785 | 7000 | 0.1969 | |
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| 0.2055 | 1.0484 | 7500 | 0.1961 | |
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| 0.2074 | 1.1183 | 8000 | 0.1980 | |
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| 0.2066 | 1.1881 | 8500 | 0.1938 | |
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| 0.2077 | 1.2580 | 9000 | 0.1937 | |
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| 0.196 | 1.3279 | 9500 | 0.1948 | |
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| 0.2027 | 1.3978 | 10000 | 0.1931 | |
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| 0.2001 | 1.4677 | 10500 | 0.1922 | |
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| 0.1925 | 1.5376 | 11000 | 0.1932 | |
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| 0.1933 | 1.6075 | 11500 | 0.1900 | |
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| 0.2038 | 1.6774 | 12000 | 0.1921 | |
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| 0.1892 | 1.7473 | 12500 | 0.1914 | |
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| 0.1956 | 1.8172 | 13000 | 0.1904 | |
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| 0.1956 | 1.8871 | 13500 | 0.1898 | |
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| 0.1925 | 1.9569 | 14000 | 0.1902 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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