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--- |
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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: poem-gen-t5-small_v1 |
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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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# poem-gen-t5-small_v1 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7290 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 3.5397 | 0.32 | 5000 | 3.3474 | |
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| 3.4107 | 0.63 | 10000 | 3.2260 | |
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| 3.3236 | 0.95 | 15000 | 3.1414 | |
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| 3.25 | 1.26 | 20000 | 3.0884 | |
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| 3.2055 | 1.58 | 25000 | 3.0461 | |
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| 3.1677 | 1.89 | 30000 | 3.0057 | |
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| 3.1189 | 2.21 | 35000 | 2.9786 | |
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| 3.0972 | 2.53 | 40000 | 2.9533 | |
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| 3.0855 | 2.84 | 45000 | 2.9318 | |
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| 3.0364 | 3.16 | 50000 | 2.9124 | |
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| 3.0125 | 3.47 | 55000 | 2.8962 | |
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| 2.9987 | 3.79 | 60000 | 2.8812 | |
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| 2.9734 | 4.1 | 65000 | 2.8675 | |
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| 2.9782 | 4.42 | 70000 | 2.8563 | |
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| 2.9492 | 4.74 | 75000 | 2.8446 | |
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| 2.9383 | 5.05 | 80000 | 2.8360 | |
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| 2.9322 | 5.37 | 85000 | 2.8250 | |
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| 2.9193 | 5.68 | 90000 | 2.8159 | |
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| 2.9119 | 6.0 | 95000 | 2.8095 | |
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| 2.8893 | 6.31 | 100000 | 2.8046 | |
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| 2.8927 | 6.63 | 105000 | 2.7975 | |
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| 2.8944 | 6.95 | 110000 | 2.7879 | |
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| 2.8568 | 7.26 | 115000 | 2.7856 | |
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| 2.8648 | 7.58 | 120000 | 2.7808 | |
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| 2.8534 | 7.89 | 125000 | 2.7737 | |
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| 2.8563 | 8.21 | 130000 | 2.7696 | |
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| 2.8387 | 8.52 | 135000 | 2.7664 | |
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| 2.8328 | 8.84 | 140000 | 2.7643 | |
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| 2.8137 | 9.16 | 145000 | 2.7615 | |
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| 2.8058 | 9.47 | 150000 | 2.7548 | |
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| 2.8138 | 9.79 | 155000 | 2.7547 | |
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| 2.8098 | 10.1 | 160000 | 2.7506 | |
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| 2.7944 | 10.42 | 165000 | 2.7479 | |
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| 2.809 | 10.73 | 170000 | 2.7443 | |
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| 2.7897 | 11.05 | 175000 | 2.7431 | |
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| 2.7955 | 11.37 | 180000 | 2.7403 | |
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| 2.793 | 11.68 | 185000 | 2.7403 | |
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| 2.798 | 12.0 | 190000 | 2.7351 | |
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| 2.7955 | 12.31 | 195000 | 2.7351 | |
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| 2.785 | 12.63 | 200000 | 2.7329 | |
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| 2.7701 | 12.94 | 205000 | 2.7329 | |
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| 2.7744 | 13.26 | 210000 | 2.7317 | |
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| 2.7827 | 13.58 | 215000 | 2.7295 | |
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| 2.7793 | 13.89 | 220000 | 2.7303 | |
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| 2.7782 | 14.21 | 225000 | 2.7298 | |
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| 2.7762 | 14.52 | 230000 | 2.7289 | |
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| 2.7719 | 14.84 | 235000 | 2.7292 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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