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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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- 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-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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# flan-t5-large-v1 |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1673 |
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- Rouge1: 74.1287 |
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- Rouge2: 66.4339 |
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- Rougel: 72.8596 |
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- Rougelsum: 73.8679 |
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- Gen Len: 16.3241 |
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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: 8 |
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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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- lr_scheduler_warmup_steps: 200 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 12.4521 | 0.85 | 200 | 0.2565 | 72.2564 | 62.6872 | 70.741 | 72.0604 | 15.9467 | |
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| 0.2538 | 1.7 | 400 | 0.1877 | 72.8835 | 64.0804 | 71.5277 | 72.642 | 16.3582 | |
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| 0.1804 | 2.55 | 600 | 0.1715 | 73.307 | 64.5027 | 72.2345 | 73.098 | 16.1429 | |
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| 0.1516 | 3.4 | 800 | 0.1675 | 73.9648 | 65.6244 | 72.8421 | 73.8516 | 16.2026 | |
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| 0.1331 | 4.26 | 1000 | 0.1609 | 73.7382 | 65.6094 | 72.5124 | 73.5658 | 16.3198 | |
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| 0.1205 | 5.11 | 1200 | 0.1656 | 74.2505 | 66.5083 | 73.1059 | 74.0956 | 16.3795 | |
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| 0.1113 | 5.96 | 1400 | 0.1593 | 74.2997 | 66.2497 | 73.2158 | 74.1265 | 16.3326 | |
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| 0.1031 | 6.81 | 1600 | 0.1643 | 74.2861 | 66.3972 | 73.1252 | 74.0796 | 16.2729 | |
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| 0.0909 | 7.66 | 1800 | 0.1638 | 73.7071 | 65.61 | 72.4082 | 73.5071 | 16.3262 | |
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| 0.0876 | 8.51 | 2000 | 0.1667 | 74.1477 | 66.0628 | 72.9115 | 73.9177 | 16.3198 | |
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| 0.0911 | 9.36 | 2200 | 0.1673 | 74.1287 | 66.4339 | 72.8596 | 73.8679 | 16.3241 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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