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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-large |
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tags: |
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- text2textgeneration |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-large-finetune-medicine-v5 |
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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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# flan-t5-large-finetune-medicine-v5 |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3517 |
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- Rouge1: 27.7218 |
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- Rouge2: 10.9162 |
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- Rougel: 23.6057 |
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- Rougelsum: 23.2999 |
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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: 5.6e-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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| No log | 1.0 | 5 | 2.2465 | 14.6773 | 3.5979 | 13.871 | 14.2474 | |
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| No log | 2.0 | 10 | 2.1106 | 10.2078 | 2.1164 | 10.2919 | 10.276 | |
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| No log | 3.0 | 15 | 2.0535 | 16.7761 | 1.5873 | 16.7952 | 17.1838 | |
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| No log | 4.0 | 20 | 2.0323 | 16.6844 | 1.5873 | 16.8444 | 16.9094 | |
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| No log | 5.0 | 25 | 2.0063 | 17.2911 | 2.3045 | 14.8127 | 15.3235 | |
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| No log | 6.0 | 30 | 2.0079 | 15.3197 | 4.6561 | 14.278 | 14.8369 | |
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| No log | 7.0 | 35 | 2.0319 | 15.9877 | 5.8947 | 13.9837 | 14.1814 | |
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| No log | 8.0 | 40 | 2.0748 | 23.1763 | 10.5 | 20.2887 | 20.2578 | |
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| No log | 9.0 | 45 | 2.1303 | 21.1874 | 6.9444 | 19.0088 | 18.991 | |
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| No log | 10.0 | 50 | 2.1746 | 20.2807 | 6.2865 | 18.2145 | 18.1012 | |
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| No log | 11.0 | 55 | 2.1729 | 21.8364 | 9.8421 | 18.7897 | 18.8242 | |
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| No log | 12.0 | 60 | 2.2083 | 22.777 | 10.9162 | 21.3444 | 21.1464 | |
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| No log | 13.0 | 65 | 2.2658 | 21.7641 | 10.9162 | 20.3906 | 19.8167 | |
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| No log | 14.0 | 70 | 2.2889 | 21.7641 | 10.9162 | 20.3906 | 19.8167 | |
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| No log | 15.0 | 75 | 2.2998 | 25.3171 | 10.9162 | 21.3683 | 20.9228 | |
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| No log | 16.0 | 80 | 2.3082 | 26.0279 | 10.9162 | 21.9565 | 21.7519 | |
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| No log | 17.0 | 85 | 2.3166 | 26.0279 | 10.9162 | 21.9565 | 21.7519 | |
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| No log | 18.0 | 90 | 2.3325 | 27.7218 | 10.9162 | 23.6057 | 23.2999 | |
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| No log | 19.0 | 95 | 2.3462 | 27.7218 | 10.9162 | 23.6057 | 23.2999 | |
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| No log | 20.0 | 100 | 2.3517 | 27.7218 | 10.9162 | 23.6057 | 23.2999 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.1 |
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- Tokenizers 0.13.3 |
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