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README.md
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---
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license: apache-2.0
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tags:
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- summarization
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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: t5-v1_1-small-finetuned-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: train
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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: 0.40608242084369006
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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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# t5-v1_1-small-finetuned-samsum
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This model is a fine-tuned version of [google/t5-v1_1-small](https://huggingface.co/google/t5-v1_1-small) on the samsum dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.0053
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- Rouge1: 0.4061
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- Rouge2: 0.1804
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- Rougel: 0.3478
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- Rougelsum: 0.3774
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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: 4
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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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| 3.9788 | 1.0 | 1842 | 2.2499 | 0.3743 | 0.1569 | 0.3191 | 0.3486 |
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| 2.9091 | 2.0 | 3684 | 2.1052 | 0.3875 | 0.1680 | 0.3329 | 0.3607 |
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| 2.6807 | 3.0 | 5526 | 2.0270 | 0.4009 | 0.1778 | 0.3439 | 0.3734 |
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| 2.5917 | 4.0 | 7368 | 2.0053 | 0.4061 | 0.1804 | 0.3478 | 0.3774 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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