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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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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-small-finetune-medicine-v4 |
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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-small-finetune-medicine-v4 |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7404 |
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- Rouge1: 17.0034 |
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- Rouge2: 4.9383 |
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- Rougel: 16.8615 |
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- Rougelsum: 16.6931 |
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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 | 2.8864 | 15.7685 | 5.117 | 15.7138 | 15.518 | |
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| No log | 2.0 | 10 | 2.8754 | 15.7702 | 5.117 | 15.6758 | 15.5641 | |
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| No log | 3.0 | 15 | 2.8556 | 15.9322 | 4.0564 | 15.9587 | 15.8195 | |
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| No log | 4.0 | 20 | 2.8469 | 16.4117 | 4.9383 | 16.3008 | 16.2258 | |
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| No log | 5.0 | 25 | 2.8380 | 17.2745 | 4.9383 | 17.2039 | 17.0175 | |
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| No log | 6.0 | 30 | 2.8276 | 16.8416 | 5.6437 | 16.737 | 16.5215 | |
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| No log | 7.0 | 35 | 2.8118 | 17.0703 | 4.9383 | 16.9715 | 16.7941 | |
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| No log | 8.0 | 40 | 2.8010 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 9.0 | 45 | 2.7898 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 10.0 | 50 | 2.7783 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 11.0 | 55 | 2.7694 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 12.0 | 60 | 2.7617 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 13.0 | 65 | 2.7546 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 14.0 | 70 | 2.7478 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 15.0 | 75 | 2.7437 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 16.0 | 80 | 2.7417 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 17.0 | 85 | 2.7416 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 18.0 | 90 | 2.7409 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 19.0 | 95 | 2.7405 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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| No log | 20.0 | 100 | 2.7404 | 17.0034 | 4.9383 | 16.8615 | 16.6931 | |
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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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