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--- |
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license: apache-2.0 |
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datasets: |
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- stacked-summaries/stacked-samsum-1024 |
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language: |
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- en |
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metrics: |
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- rouge |
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tags: |
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- stacked summaries |
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- samsum |
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pipeline_tag: summarization |
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--- |
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# flan-t5-small-stacked-samsum-1024 |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the `stacked-summaries/stacked-samsum-1024` dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7573 |
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- Rouge1: 46.6072 |
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- Rouge2: 19.9754 |
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- Rougel: 35.2715 |
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- Rougelsum: 43.3599 |
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- Gen Len: 72.64 |
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## Model Description |
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Trained on a summarization task with _potentially_ multiple doc-summary pairs stacked on top of each other. |
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You can separate its predictions by using it's special token `[NEXT_CONCEPT]` to split the output into "separate topics". |
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## Intended use & limitations |
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- This is intended to be used as a baseline/reference for comparison with the larger models. |
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## Training and evaluation data |
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See `stacked-summaries/stacked-samsum-1024`. |
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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: 0.0001 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 22138 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 3.0 |
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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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| 1.9011 | 1.0 | 230 | 1.7986 | 45.4597 | 19.6956 | 34.6878 | 42.3724 | 74.16 | |
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| 1.8297 | 2.0 | 460 | 1.7609 | 46.0427 | 20.2299 | 35.2076 | 43.0549 | 70.56 | |
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| 1.7637 | 3.0 | 690 | 1.7573 | 46.6072 | 19.9754 | 35.2715 | 43.3599 | 72.64 | |
