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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
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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: 21.1255
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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
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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: 3.4337
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- Rouge1: 21.1255
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- Rouge2: 4.2863
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- Rougel: 18.1386
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- Rougelsum: 19.8077
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- Gen Len: 15.23
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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: 0.01
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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: 1
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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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| No log | 1.0 | 13 | 3.4337 | 21.1255 | 4.2863 | 18.1386 | 19.8077 | 15.23 |
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### Framework versions
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- Transformers 4.41.0
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- Pytorch 2.2.1
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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