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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: 47.6993 |
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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: 1.3538 |
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- Rouge1: 47.6993 |
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- Rouge2: 24.0887 |
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- Rougel: 40.2819 |
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- Rougelsum: 43.8375 |
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- Gen Len: 17.0842 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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| 1.4327 | 1.0 | 1841 | 1.3620 | 47.1926 | 23.4593 | 39.7385 | 43.2514 | 17.0623 | |
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| 1.3235 | 2.0 | 3683 | 1.3563 | 46.7874 | 23.1964 | 39.4248 | 42.9616 | 16.9585 | |
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| 1.2477 | 3.0 | 5524 | 1.3538 | 47.6993 | 24.0887 | 40.2819 | 43.8375 | 17.0842 | |
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| 1.208 | 4.0 | 7366 | 1.3555 | 47.6355 | 24.0054 | 40.1665 | 43.6581 | 17.0965 | |
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| 1.193 | 5.0 | 9205 | 1.3563 | 47.6582 | 23.9906 | 40.1561 | 43.7082 | 17.1477 | |
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### Framework versions |
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- Transformers 4.36.1 |
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- Pytorch 2.1.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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