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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- samsum |
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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-base-samsum-farag |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: samsum |
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type: samsum |
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config: samsum |
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split: test |
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args: samsum |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 47.4352 |
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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-base-samsum-farag |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3695 |
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- Rouge1: 47.4352 |
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- Rouge2: 23.613 |
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- Rougel: 39.8977 |
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- Rougelsum: 43.5852 |
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- Gen Len: 17.3529 |
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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: 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: 5 |
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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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| 1.4497 | 1.0 | 1842 | 1.3848 | 46.3358 | 22.5925 | 38.7161 | 42.6084 | 17.2918 | |
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| 1.3474 | 2.0 | 3684 | 1.3717 | 47.1291 | 23.2809 | 39.4633 | 43.3246 | 17.2735 | |
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| 1.2818 | 3.0 | 5526 | 1.3701 | 47.349 | 23.4894 | 39.7933 | 43.4507 | 17.2479 | |
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| 1.2285 | 4.0 | 7368 | 1.3695 | 47.4352 | 23.613 | 39.8977 | 43.5852 | 17.3529 | |
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| 1.196 | 5.0 | 9210 | 1.3735 | 47.3488 | 23.6475 | 39.6788 | 43.523 | 17.3138 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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