--- license: apache-2.0 base_model: google/t5-v1_1-small tags: - generated_from_trainer model-index: - name: google-t5-v1_1-small-intra_model results: [] --- # google-t5-v1_1-small-intra_model 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. It achieves the following results on the evaluation set: - Loss: 0.6973 - 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] - Train Loss: 0.7164 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0001 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Losses | Train Loss | |:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:----------:| | 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, 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0.8888888888888888, 0.8888888888888888, 0.8125, 0.6666666666666666, 1.0, 1.0, 0.8888888888888888, 1, 0.8461538461538461, 1.0] | 1.0697 | | 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 | | 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, 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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 | | 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, 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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 | | 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 | ### Framework versions - Transformers 4.34.0 - Pytorch 2.1.0+cu121 - Datasets 2.6.1 - Tokenizers 0.14.1