End of training
Browse files- README.md +15 -8
- config.json +32 -0
- generation_config.json +9 -0
- pytorch_model.bin +3 -0
- training_args.bin +1 -1
README.md
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This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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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:
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### Training results
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### Framework versions
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This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6973
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- Losses: [0.4, 0.8, 0.8, 1, 0.0, 0.6000000000000001, 0.8, 0.8, 0.6000000000000001, 1.0, 1, 1, 1.0, 1, 1.0, 0.6000000000000001, 0.4, 0.2, 0.6000000000000001, 0.8, 0.8, 0.0, 0.8, 0.8, 0.6000000000000001, 1, 0.8, 0.8, 1, 0.8, 0.4, 0.8, 0.8, 0.4, 1, 1, 0.4, 0.8, 0.2, 1, 1, 0.4, 1, 1, 0.8, 1, 1, 1, 1, 0.6000000000000001, 1, 0.8, 0.0, 0.8, 0.0, 0.8, 1, 1, 0.4, 0.4, 0.2, 0.4, 0.8, 0.8, 0.4, 1, 0.2, 0.4, 0.8, 1, 1, 0.6000000000000001, 0.8, 0.8, 0.6000000000000001, 0.8, 1, 0.8, 1, 0.0, 1, 0.0, 0.8, 0.8, 0.8, 1, 0.8, 0.8, 0.4, 1, 0.8, 0.8, 0.8, 0.8, 0.0, 1, 0.8, 0.6000000000000001, 0.0, 1, 0.8, 1, 1, 1, 1, 0.0, 0.8, 1, 1, 0.8, 1, 1, 1, 0.4, 0.4, 1, 1, 0.8, 0.8, 0.6000000000000001, 0.0, 0.6000000000000001, 0.2, 1.0, 0.8, 0.8, 0.8, 1, 0.8, 0.8, 0.6000000000000001, 1, 0.8, 0.8, 1, 1, 0.8, 0.6000000000000001, 0.4, 0.8, 0.0, 0.2, 0.8, 0.8, 0.6000000000000001, 0.8, 1, 0.8, 0.4, 1, 1, 1.0, 0.8, 0.8, 1, 1, 1, 0.8, 1.0, 0.4, 0.8, 0.4, 1, 0.4, 0.0, 0.8, 0.8, 0.0, 1, 0.8, 1, 0.6000000000000001, 1, 1.0, 0.8, 1.0, 0.4, 0.4, 0.8, 0.8, 0.6000000000000001, 1, 0.4, 1, 1, 0.2, 0.0, 0.6000000000000001, 0.4, 0.2, 0.2, 0.8, 0.8, 0.8, 1, 0.8, 1, 1, 0.8, 0.8, 0.6000000000000001, 0.4, 1, 0.4, 0.0, 1, 0.8, 0.2, 0.6000000000000001, 0.6000000000000001, 0.2, 0.4, 0.8, 0.6000000000000001, 1.0, 0.8, 1, 0.8, 0.8, 0.8, 0.8, 0.4, 0.4, 1, 0.8, 0.2, 0.2, 1, 0.8, 0.8, 0.8, 1, 1, 0.0, 0.4, 0.6000000000000001, 1, 1, 0.8, 0.8, 0.8, 0.8, 1, 0.8, 0.8, 0.4, 1, 0.4, 1, 1, 0.8, 1, 1, 0.8, 0.8, 0.0, 0.4, 1, 1, 1.0, 1, 0.8, 0.4, 1, 0.6000000000000001, 1, 0.0, 1, 1, 0.8, 0.8, 0.6000000000000001, 1, 1, 0.2, 0.8, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.8, 0.4, 1, 0.2, 0.8, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.4, 1, 0.4, 0.0, 1, 1, 0.8, 1, 1, 0.8, 1, 0.2, 0.4, 0.8, 0.6000000000000001, 0.8, 0.4, 0.4, 0.8, 1, 0.0, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.0, 0.8, 1, 0.8, 0.8, 0.8, 0.4, 0.4, 0.8, 1, 1, 1, 0.6000000000000001, 0.0, 0.8, 0.8, 0.8, 0.4, 1, 1, 0.4, 0.4, 0.8, 0.8, 1, 0.4, 0.2, 0.6000000000000001, 1, 1, 1, 0.8, 1, 1, 0.8, 0.4, 0.4, 0.8, 1, 0.8, 1, 0.4, 0.6000000000000001, 0.4, 1]
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- Train Loss: 0.7164
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## Model description
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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: 30
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Losses | Train Loss |
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| 13.7913 | 1.0 | 99 | 11.9227 | [1.0, 1.0, 1, 1, 1.0, 1.0, 1, 0.8888888888888888, 0.875, 0.8461538461538461, 0.875, 0.8888888888888888, 1.0, 0.8, 1.0, 0.8888888888888888, 1.0, 1.0, 1, 1.0, 1, 1.0, 1.0, 1.0, 1.0, 0.85, 1.0, 1.0, 0.8235294117647058, 0.5555555555555556, 0.8888888888888888, 1, 1.0, 10.0, 1, 0.8888888888888888, 1.0, 1.0, 1.0, 0.8888888888888888, 1.0, 1, 0.8571428571428571, 0.6666666666666666, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 1.0, 0.8, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.8888888888888888, 1, 1.0, 0.8888888888888888, 1.0, 1, 1, 0.5555555555555556, 1.0, 1.0, 1.0, 1.0, 1, 0.8235294117647058, 1.0, 0.3333333333333333, 1.0, 0.8888888888888888, 0.8571428571428571, 1, 1, 1, 1.0, 0.8, 1.0, 1.0, 1, 1.0, 1, 0.9090909090909091, 0.875, 1.0, 1, 1.0, 0.8461538461538461, 1.0, 1.0, 1, 0.8571428571428571, 1.0, 1, 0.8888888888888888, 0.8888888888888888, 1.0, 1.0, 1.0, 0.7777777777777778, 1, 0.8666666666666667, 1.0, 1, 0.8888888888888888, 1, 0.8888888888888888, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1.0, 1.0, 0.8888888888888888, 0.8, 0.8888888888888888, 1.0, 1.0, 1.0, 1.0, 0.875, 1.0, 1.0, 1.0, 0.8888888888888888, 0.8888888888888888, 1, 0.8, 0.8, 1.0, 1, 1, 1.0, 1.0, 1.0, 1.0, 0.8888888888888888, 1, 1.0, 1.0, 1.0, 0.8888888888888888, 0.8461538461538461, 1.0, 1.0, 0.9090909090909091, 1.0, 0.8181818181818182, 0.8, 0.8888888888888888, 0.8, 1, 1.0, 1, 0.9090909090909091, 1.0, 1.0, 1.0, 0.75, 1, 1.0, 1.0, 0.8888888888888888, 0.8235294117647058, 1.0, 1.0, 1.0, 0.8235294117647058, 1.0, 1.0, 1.0, 0.8888888888888888, 0.8235294117647058, 1.0, 1.0, 10.0, 1.0, 0.8888888888888888, 1.0, 1.0, 1, 1, 1.0, 1.0, 1, 1, 1.0, 0.8888888888888888, 1.0, 1.0, 0.8888888888888888, 0.8888888888888888, 1.0, 1.0, 0.8, 0.8888888888888888, 1.0, 1.0, 0.8888888888888888, 1.0, 0.875, 0.8888888888888888, 1.0, 0.5555555555555556, 0.8888888888888888, 1.0, 1, 0.875, 0.8888888888888888, 1.0, 10.0, 1, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1.0, 1.0, 1, 0.6666666666666666, 1.0, 1.0, 1.0, 0.8571428571428571, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.8888888888888888, 0.8888888888888888, 1.0, 0.7777777777777778, 1, 1.0, 1.0, 0.8461538461538461, 1.0, 0.8, 0.8888888888888888, 1.0, 1, 1.0, 1, 0.8, 1.0, 0.8, 0.8888888888888888, 1, 1.0, 1.0, 1.0, 1.0, 0.8181818181818182, 0.875, 0.7777777777777778, 0.8888888888888888, 10.0, 0.8888888888888888, 0.875, 1.0, 0.8888888888888888, 0.8888888888888888, 0.8, 1.0, 1.0, 1.0, 0.8888888888888888, 1.0, 1, 0.8125, 1.0, 0.9090909090909091, 1.0, 1.0, 0.8888888888888888, 1.0, 1.0, 0.8888888888888888, 0.8888888888888888, 0.75, 1, 1, 0.9090909090909091, 1.0, 0.75, 1, 0.875, 1.0, 1.0, 0.9, 1, 1.0, 0.4444444444444444, 1.0, 1, 1.0, 1, 1, 0.8888888888888888, 1.0, 1, 1.0, 0.8888888888888888, 1.0, 1.0, 1.0, 1.0, 0.8888888888888888, 1.0, 0.875, 1.0, 1.0, 1.0, 1.0, 1.0, 0.8, 1.0, 0.8888888888888888, 1.0, 1.0, 0.8888888888888888, 0.875, 0.4444444444444444, 1.0, 1.0, 1.0, 0.8888888888888888, 10.0, 0.7777777777777778, 1.0, 1.0, 1.0, 0.8461538461538461, 1, 0.8888888888888888, 0.8888888888888888, 0.8125, 0.6666666666666666, 1.0, 1.0, 0.8888888888888888, 1, 0.8461538461538461, 1.0] | 1.0697 |
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| 6.0033 | 2.0 | 198 | 4.6189 | [1, 0.8, 1, 1, 1, 1.0, 1, 0.8, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 1.0, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 1, 1, 1, 0.8, 1.0, 1, 1, 1, 1.0, 1, 1, 0.8, 1, 1, 0.8, 1, 0.8, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1.0, 1, 0.8, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 0.8, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 0.8, 1, 1.0, 1, 0.8, 0.8, 1, 0.8, 1, 1, 1, 0.8, 1, 1, 1, 0.8, 1, 1, 0.8, 1, 0.8, 1, 1, 1, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 0.8, 1, 1, 1, 0.8, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 1, 0.8, 1.0, 0.8, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 0.8, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 1, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 1, 1, 1] | 0.9694 |
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| 2.5509 | 3.0 | 297 | 1.0645 | [1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 0.4, 1.0, 0.8, 1, 1, 0.6000000000000001, 0.4, 0.4, 1.0, 1, 1, 1.0, 1, 1.0, 1.0, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 0.8, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1.0, 0.8, 1, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1.0, 0.6000000000000001, 1, 0.6000000000000001, 0.4, 1.0, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 1.0, 1.0, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.4, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.4, 0.8, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 0.6000000000000001, 1, 1, 1.0, 0.6000000000000001, 0.0, 1.0, 1, 1, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 0.6000000000000001, 0.4, 0.6000000000000001, 1, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 0.8, 1.0, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 0.6000000000000001, 1.0, 1.0, 1, 1, 1, 0.8, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 1.0, 0.0, 1.0, 0.6000000000000001, 0.6000000000000001, 1, 0.8, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 1, 1, 1, 0.6000000000000001, 0.4, 0.6000000000000001, 0.4, 1.0, 1.0, 0.6000000000000001, 0.8, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 1, 0.6000000000000001, 0.4, 1.0, 0.6000000000000001, 1, 1, 1.0, 1.0, 1, 1.0, 1.0, 1.0, 1, 0.6000000000000001, 1, 1.0, 1.0, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 1, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 0.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 1, 1.0, 1, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 1, 0.8, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.4, 1, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 1.0, 1, 0.6000000000000001, 1.0, 0.8, 0.8, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.6000000000000001, 1, 0.6000000000000001, 1.0, 1.0, 0.8, 0.6000000000000001, 0.0, 0.6000000000000001, 0.6000000000000001, 1.0, 0.8, 0.4, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1, 1, 1.0, 0.4, 1, 0.6000000000000001, 0.4, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.6000000000000001, 0.4, 1, 1, 0.4, 1.0, 1.0, 0.6000000000000001, 1.0, 1.0, 0.8, 1.0, 1.0, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1.0, 0.6000000000000001, 1.0, 1, 1.0, 0.4, 1, 1, 0.4, 0.6000000000000001, 1.0, 1, 1.0, 0.6000000000000001, 1.0, 1.0, 1.0, 0.6000000000000001, 1, 1, 1, 1, 1.0, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 1.0, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.4, 1, 1, 0.6000000000000001, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 1.0, 0.8, 1.0, 1.0, 1, 0.6000000000000001, 1.0, 0.4, 0.6000000000000001, 1] | 0.7944 |
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| 1.323 | 4.0 | 396 | 0.7302 | [0.4, 0.8, 0.4, 1, 0.4, 0.6000000000000001, 0.8, 0.8, 0.6000000000000001, 1, 1, 1, 1, 0.8, 1.0, 0.6000000000000001, 0.4, 0.8, 0.8, 1, 0.8, 0.4, 0.4, 0.8, 0.6000000000000001, 0.8, 0.8, 1, 0.8, 0.4, 0.4, 0.8, 0.8, 0.4, 1, 1, 0.4, 0.4, 0.8, 0.8, 0.8, 0.4, 1, 1, 0.4, 1, 1, 1, 0.8, 0.8, 1, 0.4, 0.4, 0.8, 0.4, 1, 1, 1, 0.4, 0.4, 0.8, 0.4, 0.8, 0.8, 0.4, 1, 0.8, 0.4, 0.8, 1, 0.8, 1.0, 1, 1, 0.8, 0.8, 0.8, 0.8, 1, 0.4, 1, 0.4, 0.4, 0.8, 0.8, 0.8, 0.8, 1, 0.0, 1, 0.4, 0.8, 0.4, 0.4, 0.4, 1, 0.8, 1.0, 0.4, 0.8, 0.4, 0.8, 1, 0.8, 0.8, 0.4, 0.8, 1, 1, 0.8, 0.8, 0.8, 0.8, 0.4, 0.4, 1, 1, 0.4, 0.8, 0.6000000000000001, 0.4, 1, 0.8, 1.0, 0.4, 0.4, 0.8, 1, 0.8, 0.8, 1.0, 0.8, 0.8, 0.8, 0.8, 1, 0.8, 0.6000000000000001, 0.4, 0.8, 0.4, 0.8, 0.8, 0.8, 0.6000000000000001, 0.8, 1, 1, 1, 0.8, 1, 0.6000000000000001, 0.8, 0.8, 0.8, 1, 1, 1, 0.6000000000000001, 0.4, 0.8, 0.0, 1, 0.6000000000000001, 0.4, 0.8, 0.4, 0.4, 1, 1, 1, 0.8, 0.8, 1.0, 0.8, 1.0, 0.4, 0.4, 0.4, 1, 1.0, 0.8, 0.0, 0.8, 1, 0.8, 0.4, 0.6000000000000001, 0.4, 0.8, 0.8, 0.8, 1, 1, 0.8, 0.8, 1, 1, 0.8, 0.8, 1.0, 0.4, 1, 0.4, 0.4, 1, 0.8, 0.8, 0.8, 1, 0.8, 0.4, 0.8, 0.8, 0.6000000000000001, 0.4, 0.8, 0.8, 1, 0.8, 0.8, 0.4, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 1, 0.8, 1, 0.8, 0.4, 0.4, 0.6000000000000001, 1, 1, 0.8, 0.8, 1.0, 1, 1, 0.8, 0.8, 0.4, 1, 0.6000000000000001, 0.8, 1, 0.8, 0.8, 0.8, 0.8, 0.8, 0.4, 0.4, 1, 0.8, 0.6000000000000001, 0.8, 0.8, 0.4, 1, 0.6000000000000001, 0.8, 0.4, 0.8, 1, 0.8, 0.8, 0.6000000000000001, 1, 0.8, 0.8, 0.4, 0.6000000000000001, 0.8, 0.8, 0.6000000000000001, 0.8, 0.4, 1.0, 0.8, 0.4, 1.0, 0.8, 1, 0.6000000000000001, 0.4, 1, 0.4, 0.4, 1, 1, 1, 1, 0.8, 0.4, 1, 0.8, 0.0, 0.8, 1.0, 0.8, 0.4, 0.4, 0.4, 1, 0.4, 0.6000000000000001, 0.8, 1, 1, 0.4, 0.8, 1, 1, 0.4, 0.8, 0.4, 0.4, 0.8, 1, 1, 1, 0.8, 0.4, 0.8, 0.4, 0.8, 0.4, 1, 1, 0.4, 0.4, 0.8, 0.4, 0.8, 0.4, 0.8, 0.6000000000000001, 1, 1, 0.8, 0.8, 1, 1, 0.4, 0.4, 0.6000000000000001, 0.4, 1, 0.8, 0.8, 0.4, 0.6000000000000001, 0.0, 1] | 0.7365 |
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55 |
+
| 1.1398 | 5.0 | 495 | 0.6483 | [0.4, 0.8, 0.4, 1, 0.4, 0.6000000000000001, 0.8, 0.8, 0.6000000000000001, 1, 1, 1, 1, 0.8, 1.0, 0.6000000000000001, 0.4, 0.8, 0.8, 1, 0.8, 0.4, 0.4, 0.8, 0.6000000000000001, 0.8, 0.8, 1, 0.8, 0.4, 0.4, 0.8, 0.8, 0.4, 1, 1, 0.4, 0.4, 0.8, 0.8, 0.8, 0.4, 1, 1, 0.4, 1, 1, 1, 0.8, 0.8, 1, 0.4, 0.4, 0.8, 0.4, 1, 1, 1, 0.4, 0.4, 0.8, 0.4, 0.8, 0.8, 0.4, 1, 0.8, 0.4, 0.8, 1, 0.8, 1.0, 1, 1, 0.8, 0.8, 0.8, 0.8, 1, 0.4, 1, 0.4, 0.4, 0.8, 0.8, 0.8, 0.8, 1, 0.0, 1, 0.4, 0.8, 0.4, 0.4, 0.4, 1, 0.8, 1.0, 0.4, 0.8, 0.4, 0.8, 1, 0.8, 0.8, 0.4, 0.8, 1, 1, 0.8, 0.8, 0.8, 0.8, 0.4, 0.4, 1, 1, 0.4, 0.8, 0.6000000000000001, 0.4, 1, 0.8, 1.0, 0.4, 0.4, 0.8, 1, 0.8, 0.8, 1.0, 0.8, 0.8, 0.8, 0.8, 1, 0.8, 0.6000000000000001, 0.4, 0.8, 0.4, 0.8, 0.8, 0.8, 0.6000000000000001, 0.8, 1, 1, 1, 0.8, 1, 0.6000000000000001, 0.8, 0.8, 0.8, 1, 1, 1, 0.6000000000000001, 0.4, 0.8, 0.0, 1, 0.6000000000000001, 0.4, 0.8, 0.4, 0.4, 1, 1, 1, 0.8, 0.8, 1.0, 0.8, 1.0, 0.4, 0.4, 0.4, 1, 1.0, 0.8, 0.0, 0.8, 1, 0.8, 0.4, 0.6000000000000001, 0.4, 0.8, 0.8, 0.8, 1, 1, 0.8, 0.8, 1, 1, 0.8, 0.8, 1.0, 0.4, 1, 0.4, 0.4, 1, 0.8, 0.8, 0.8, 1, 0.8, 0.4, 0.8, 0.8, 0.6000000000000001, 0.4, 0.8, 0.8, 1, 0.8, 0.8, 0.4, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 1, 0.8, 1, 0.8, 0.4, 0.4, 0.6000000000000001, 1, 1, 0.8, 0.8, 1.0, 1, 1, 0.8, 0.8, 0.4, 1, 0.6000000000000001, 0.8, 1, 0.8, 0.8, 0.8, 0.8, 0.8, 0.4, 0.4, 1, 0.8, 0.6000000000000001, 0.8, 0.8, 0.4, 1, 0.6000000000000001, 0.8, 0.4, 0.8, 1, 0.8, 0.8, 0.6000000000000001, 1, 0.8, 0.8, 0.4, 0.6000000000000001, 0.8, 0.8, 0.6000000000000001, 0.8, 0.4, 1.0, 0.8, 0.4, 1.0, 0.8, 1, 0.6000000000000001, 0.4, 1, 0.4, 0.4, 1, 1, 1, 1, 0.8, 0.4, 1, 0.8, 0.0, 0.8, 1.0, 0.8, 0.4, 0.4, 0.4, 1, 0.4, 0.6000000000000001, 0.8, 1, 1, 0.4, 0.8, 1, 1, 0.4, 0.8, 0.4, 0.4, 0.8, 1, 1, 1, 0.8, 0.4, 0.8, 0.4, 0.8, 0.4, 1, 1, 0.4, 0.4, 0.8, 0.4, 0.8, 0.4, 0.8, 0.6000000000000001, 1, 1, 1, 0.8, 1, 1, 0.4, 0.4, 0.6000000000000001, 0.4, 1, 0.8, 0.8, 0.4, 0.6000000000000001, 0.0, 1] | 0.7370 |
|
56 |
+
| 0.9565 | 6.0 | 594 | 0.6207 | [0.0, 0.8, 0.0, 1, 0.4, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 1.0, 1, 1, 1, 1, 1.0, 0.6000000000000001, 0.4, 0.2, 0.2, 1, 0.8, 0.0, 0.4, 0.8, 0.6000000000000001, 1, 1, 1, 1, 0.0, 0.0, 0.8, 0.8, 0.4, 1, 1, 0.4, 0.0, 1, 1, 1, 0.4, 1, 1, 0.4, 1, 1, 1, 0.8, 0.8, 1, 0.4, 0.0, 0.8, 0.4, 1, 1, 1, 0.4, 0.4, 0.2, 0.4, 1, 0.8, 0.4, 1, 0.2, 0.0, 1, 1, 1, 1.0, 1, 1, 0.6000000000000001, 0.8, 1, 0.8, 1, 0.0, 1, 0.0, 0.4, 0.8, 0.8, 1, 0.2, 1, 0.0, 1, 0.8, 1, 0.4, 0.8, 0.4, 1, 0.8, 1.0, 0.0, 1, 0.4, 0.8, 1, 1, 1, 0.0, 0.2, 1, 1, 0.8, 1, 0.8, 1, 0.4, 0.4, 1, 1, 0.4, 0.8, 0.6000000000000001, 0.4, 0.6000000000000001, 0.2, 1.0, 0.4, 0.8, 0.8, 1, 0.8, 0.8, 1.0, 1, 0.8, 0.8, 1, 1, 1, 0.4, 0.4, 0.8, 0.0, 0.2, 0.8, 0.8, 0.6000000000000001, 0.8, 1, 1, 0.4, 0.8, 1, 0.6000000000000001, 0.8, 0.8, 1, 1, 1, 1, 1.0, 0.4, 1, 0.4, 1, 0.4, 0.4, 0.8, 0.8, 0.4, 1, 0.4, 1, 0.2, 1, 1.0, 0.8, 1.0, 0.4, 0.4, 0.4, 1, 1.0, 1, 0.4, 1, 1, 0.2, 0.4, 0.6000000000000001, 0.4, 0.8, 0.2, 0.8, 1, 1, 0.2, 0.8, 1, 1, 0.2, 0.8, 0.2, 0.4, 1, 0.4, 0.4, 1, 0.8, 0.2, 0.6000000000000001, 1, 0.8, 0.4, 0.8, 0.8, 1.0, 0.8, 1, 0.8, 1, 1, 0.8, 0.4, 0.4, 0.8, 0.8, 0.2, 0.2, 0.8, 0.8, 1, 0.8, 1, 1, 0.4, 0.4, 0.6000000000000001, 1, 1, 0.8, 0.8, 1.0, 1, 1, 0.8, 0.8, 0.4, 1, 0.4, 1, 1, 0.8, 1, 1, 0.8, 0.8, 0.0, 0.4, 1, 1, 1.0, 1, 0.8, 0.4, 1, 0.6000000000000001, 1, 0.4, 1, 1, 0.8, 0.8, 0.6000000000000001, 1, 0.8, 0.2, 0.0, 0.6000000000000001, 0.2, 0.8, 0.6000000000000001, 0.8, 0.8, 1.0, 0.2, 0.4, 1.0, 0.8, 1, 0.6000000000000001, 0.4, 1, 0.4, 0.4, 1, 1, 1, 1, 1, 0.8, 1, 0.2, 0.0, 0.8, 1.0, 0.8, 0.0, 0.8, 0.4, 1, 0.0, 0.6000000000000001, 0.6000000000000001, 1, 1, 0.4, 0.6000000000000001, 1, 1, 0.8, 0.8, 0.0, 0.4, 0.8, 1, 0.4, 0.4, 0.6000000000000001, 0.0, 0.8, 0.4, 0.8, 0.4, 1, 1, 0.8, 0.4, 1, 0.4, 1, 0.4, 0.8, 0.6000000000000001, 1, 1, 1, 0.8, 1, 1, 0.8, 0.4, 0.6000000000000001, 0.4, 1, 0.8, 0.8, 0.4, 0.6000000000000001, 0.0, 1] | 0.7070 |
|
57 |
+
| 0.8479 | 7.0 | 693 | 0.5786 | [0.0, 1, 0.0, 0.4, 0.8, 1.0, 0.8, 1, 0.6000000000000001, 1.0, 1, 0.4, 1, 1, 1, 0.6000000000000001, 0.4, 0.2, 0.2, 1, 0.2, 0.0, 0.0, 0.8, 0.6000000000000001, 1, 1, 1, 1, 0.0, 0.0, 0.8, 0.8, 0.4, 1, 1, 1, 0.0, 1, 1, 1, 0.4, 1, 0.4, 0.0, 1, 1, 1, 1, 0.6000000000000001, 1, 0.0, 0.0, 1, 0.0, 1, 1, 1, 0.0, 0.4, 0.2, 0.4, 1, 1, 1, 1, 0.2, 0.0, 1, 1, 1, 1.0, 1, 1, 0.6000000000000001, 0.8, 1, 1, 1, 0.0, 1, 0.0, 0.0, 0.8, 0.2, 1, 0.2, 1.0, 0.4, 1, 0.8, 1, 0.0, 1, 0.0, 1, 0.8, 1.0, 0.0, 1, 1, 0.2, 1, 1, 1, 0.0, 0.2, 1, 1, 0.8, 1, 0.2, 1, 0.4, 0.8, 1, 1, 1, 1, 1.0, 0.4, 0.6000000000000001, 0.2, 1, 0.8, 0.8, 1, 1, 1, 1, 1.0, 1, 0.2, 0.8, 1, 1, 1, 0.4, 0.4, 0.8, 0.0, 0.2, 1, 1, 0.4, 1, 1, 1, 0.4, 0.2, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 0.4, 1, 0.4, 0.0, 1, 0.8, 0.4, 1, 0.4, 1, 0.2, 1, 1.0, 1, 1.0, 1, 0.0, 0.8, 1, 1.0, 1, 0.4, 1, 1, 0.2, 0.8, 0.6000000000000001, 0.4, 1, 0.2, 0.2, 1, 1, 0.2, 1, 1, 1, 0.2, 1, 0.2, 0.4, 1, 0.4, 1, 1.0, 1, 0.2, 0.6000000000000001, 1.0, 0.8, 0.4, 1, 0.6000000000000001, 1.0, 0.8, 1, 1, 1, 1, 1, 0.4, 0.4, 1, 1, 0.2, 1, 1, 1, 1, 1, 1, 1, 0.8, 0.0, 0.6000000000000001, 1, 1, 1, 1, 0.8, 1, 1, 0.4, 0.8, 1, 1, 0.4, 1, 1, 0.6000000000000001, 1, 1, 1, 1, 0.0, 0.4, 1, 1, 1.0, 1, 1, 1, 1, 0.6000000000000001, 1, 0.8, 1, 1, 0.8, 1, 0.6000000000000001, 1, 0.2, 0.2, 0.0, 1, 0.2, 1, 0.6000000000000001, 1, 0.8, 1, 0.2, 0.8, 1, 0.2, 1, 0.6000000000000001, 0.0, 1, 0.8, 0.0, 1, 1, 1, 1, 1, 0.8, 1, 0.2, 0.4, 0.8, 1, 0.2, 0.0, 0.8, 0.0, 1, 0.0, 0.6000000000000001, 0.6000000000000001, 1, 1, 1, 0.6000000000000001, 1, 1.0, 1, 0.8, 0.0, 0.4, 1, 1, 0.4, 0.4, 0.6000000000000001, 0.0, 1, 0.0, 1, 0.8, 1, 1, 0.8, 0.8, 1, 0.0, 1, 0.8, 1, 1, 1, 0.4, 1, 1, 1, 1, 0.8, 0.0, 0.4, 0.0, 1.0, 0.2, 1, 0.4, 0.6000000000000001, 0.4, 1] | 0.7231 |
|
58 |
+
| 0.7582 | 8.0 | 792 | 0.6239 | [0.4, 1, 0.4, 1, 1, 0.6000000000000001, 0.8, 1, 0.6000000000000001, 1.0, 1.0, 0.4, 1, 0.8, 1, 1, 0.4, 0.8, 0.8, 1, 0.8, 1, 1, 1, 1, 1, 0.8, 1, 1, 0.4, 1, 0.8, 1, 0.4, 1, 1.0, 1, 0.0, 1, 0.8, 0.8, 0.4, 1, 1, 0.4, 1, 1, 1, 1, 0.6000000000000001, 1, 0.4, 0.4, 1, 0.4, 1, 1, 1, 0.4, 0.4, 0.2, 0.4, 0.8, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 0.6000000000000001, 0.8, 1, 0.8, 1, 0.0, 1, 0.0, 0.4, 0.8, 0.8, 0.8, 1, 1, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 1, 1.0, 0.4, 1, 1, 0.2, 1, 0.8, 1, 0.0, 0.8, 1, 1, 1, 1, 0.2, 1, 0.4, 0.4, 1, 1, 1, 1, 1, 0.4, 1, 1, 1.0, 1, 0.8, 1, 1, 1, 0.8, 1.0, 1, 1, 0.8, 1, 1, 1, 1, 0.4, 1, 0.4, 0.2, 1, 1, 0.6000000000000001, 1, 1, 1, 1, 0.8, 1, 1, 1, 1, 0.8, 1, 1, 1, 0.6000000000000001, 1, 0.8, 1, 1, 0.6000000000000001, 1, 1, 1, 0.4, 1, 1, 1, 0.2, 1, 1.0, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 0.8, 1, 0.2, 0.4, 1, 1, 0.8, 1, 0.8, 1, 1, 0.8, 1, 1, 1, 0.8, 1, 1.0, 1, 1, 1, 0.4, 1, 1, 0.2, 0.8, 1.0, 0.8, 0.4, 1, 0.6000000000000001, 1.0, 0.8, 0.8, 1, 1, 0.8, 1, 0.4, 0.4, 0.8, 1, 0.2, 1, 1, 1, 1, 1, 1, 1, 0.4, 1, 0.6000000000000001, 1, 1, 1, 1, 1, 1, 1, 0.8, 0.8, 1, 1, 1, 1, 1, 0.8, 1, 1, 0.8, 1, 0.0, 1, 1, 1, 1.0, 1, 1, 1, 1, 0.6000000000000001, 1, 1, 1, 1, 0.8, 1, 0.6000000000000001, 1, 1, 1, 1, 0.6000000000000001, 0.8, 0.8, 0.6000000000000001, 1, 0.4, 1, 0.8, 0.4, 1, 0.8, 1, 0.6000000000000001, 0.4, 1, 0.4, 1, 1, 1, 1, 1, 0.8, 0.4, 1, 1, 1, 0.8, 1, 1, 0.0, 0.4, 1, 1, 0.0, 0.6000000000000001, 0.8, 1, 1, 1, 1, 1, 1, 1, 0.8, 0.4, 0.4, 1, 1, 1, 1, 1, 1, 1, 1, 0.8, 0.4, 1, 1, 0.4, 0.8, 1, 0.0, 0.8, 0.4, 0.8, 1, 1, 1, 0.8, 1, 1, 1, 0.8, 0.4, 0.6000000000000001, 0.4, 1.0, 1, 0.8, 1, 0.6000000000000001, 0.0, 1] | 0.8384 |
|
59 |
+
| 0.7579 | 9.0 | 891 | 0.5293 | [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] | 0.9972 |
|
60 |
|
61 |
|
62 |
### Framework versions
|
config.json
ADDED
@@ -0,0 +1,32 @@
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|
1 |
+
{
|
2 |
+
"_name_or_path": "google/t5-v1_1-small",
|
3 |
+
"architectures": [
|
4 |
+
"CustomT5Model"
|
5 |
+
],
|
6 |
+
"classifier_dropout": 0.0,
|
7 |
+
"d_ff": 1024,
|
8 |
+
"d_kv": 64,
|
9 |
+
"d_model": 512,
|
10 |
+
"decoder_start_token_id": 0,
|
11 |
+
"dense_act_fn": "gelu_new",
|
12 |
+
"dropout_rate": 0.1,
|
13 |
+
"eos_token_id": 1,
|
14 |
+
"feed_forward_proj": "gated-gelu",
|
15 |
+
"initializer_factor": 1.0,
|
16 |
+
"is_encoder_decoder": true,
|
17 |
+
"is_gated_act": true,
|
18 |
+
"layer_norm_epsilon": 1e-06,
|
19 |
+
"model_type": "t5",
|
20 |
+
"num_decoder_layers": 8,
|
21 |
+
"num_heads": 6,
|
22 |
+
"num_layers": 8,
|
23 |
+
"output_past": true,
|
24 |
+
"pad_token_id": 0,
|
25 |
+
"relative_attention_max_distance": 128,
|
26 |
+
"relative_attention_num_buckets": 32,
|
27 |
+
"tie_word_embeddings": false,
|
28 |
+
"torch_dtype": "float16",
|
29 |
+
"transformers_version": "4.34.0",
|
30 |
+
"use_cache": true,
|
31 |
+
"vocab_size": 32128
|
32 |
+
}
|
generation_config.json
ADDED
@@ -0,0 +1,9 @@
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1 |
+
{
|
2 |
+
"decoder_start_token_id": 0,
|
3 |
+
"eos_token_id": 1,
|
4 |
+
"max_new_tokens": 5,
|
5 |
+
"min_new_tokens": 5,
|
6 |
+
"pad_token_id": 0,
|
7 |
+
"prefix_allowed_tokens_fn": "lambda a, b: [209, 204, 220, 314, 305]",
|
8 |
+
"transformers_version": "4.34.0"
|
9 |
+
}
|
pytorch_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:47808f24d546a21db20c477d5bbd2b6c0581073cdb9f284d214f21b9d6c9929c
|
3 |
+
size 153988290
|
training_args.bin
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 4728
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5fcac56f0026ecf09a232d309c909cda07744521de47e5aad926a7b2a00ea953
|
3 |
size 4728
|