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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-small-mlm-pubmed-45 |
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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-small-mlm-pubmed-45 |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6395 |
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- Rouge2 Precision: 0.3383 |
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- Rouge2 Recall: 0.2424 |
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- Rouge2 Fmeasure: 0.2753 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
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|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:| |
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| 2.519 | 0.75 | 500 | 1.9659 | 0.3178 | 0.1888 | 0.2299 | |
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| 2.169 | 1.51 | 1000 | 1.8450 | 0.3256 | 0.2138 | 0.25 | |
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| 2.0796 | 2.26 | 1500 | 1.7900 | 0.3368 | 0.2265 | 0.2636 | |
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| 1.9978 | 3.02 | 2000 | 1.7553 | 0.3427 | 0.234 | 0.2709 | |
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| 1.9686 | 3.77 | 2500 | 1.7172 | 0.3356 | 0.2347 | 0.2692 | |
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| 1.9142 | 4.52 | 3000 | 1.6986 | 0.3358 | 0.238 | 0.2715 | |
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| 1.921 | 5.28 | 3500 | 1.6770 | 0.3349 | 0.2379 | 0.2709 | |
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| 1.8848 | 6.03 | 4000 | 1.6683 | 0.3346 | 0.2379 | 0.2708 | |
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| 1.8674 | 6.79 | 4500 | 1.6606 | 0.3388 | 0.2419 | 0.2752 | |
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| 1.8606 | 7.54 | 5000 | 1.6514 | 0.3379 | 0.2409 | 0.274 | |
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| 1.8515 | 8.3 | 5500 | 1.6438 | 0.3356 | 0.2407 | 0.2731 | |
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| 1.8403 | 9.05 | 6000 | 1.6401 | 0.3367 | 0.2421 | 0.2744 | |
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| 1.8411 | 9.8 | 6500 | 1.6395 | 0.3383 | 0.2424 | 0.2753 | |
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### Framework versions |
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- Transformers 4.12.5 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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