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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: t5-base-qasper |
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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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# t5-base-qasper |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1947 |
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- Answer f1: 0.0483 |
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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: 1e-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: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Answer f1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:| |
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| No log | 1.0 | 262 | 1.4772 | 0.0433 | |
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| 1.5405 | 2.0 | 524 | 1.2919 | 0.0492 | |
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| 1.5405 | 3.0 | 786 | 1.2517 | 0.0491 | |
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| 1.1476 | 4.0 | 1048 | 1.2292 | 0.0492 | |
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| 1.1476 | 5.0 | 1310 | 1.2197 | 0.0497 | |
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| 1.056 | 6.0 | 1572 | 1.2150 | 0.0509 | |
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| 1.056 | 7.0 | 1834 | 1.2116 | 0.0507 | |
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| 0.9915 | 8.0 | 2096 | 1.2048 | 0.0503 | |
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| 0.9915 | 9.0 | 2358 | 1.2056 | 0.0512 | |
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| 0.9418 | 10.0 | 2620 | 1.1954 | 0.0497 | |
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| 0.9418 | 11.0 | 2882 | 1.1977 | 0.0491 | |
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| 0.9348 | 12.0 | 3144 | 1.1954 | 0.0486 | |
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| 0.9348 | 13.0 | 3406 | 1.1926 | 0.0482 | |
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| 0.9073 | 14.0 | 3668 | 1.1946 | 0.0486 | |
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| 0.9073 | 15.0 | 3930 | 1.1919 | 0.0480 | |
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| 0.8769 | 16.0 | 4192 | 1.1955 | 0.0485 | |
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| 0.8769 | 17.0 | 4454 | 1.1941 | 0.0481 | |
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| 0.8754 | 18.0 | 4716 | 1.1947 | 0.0483 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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