---
license: apache-2.0
tags:
- generated_from_trainer
- summarization
metrics:
- rouge
datasets:
- stacked-summaries/stacked-samsum-1024
model-index:
- name: flan-t5-large-stacked-samsum1024-WIP3
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: test
    metrics:
    - name: ROUGE-1
      type: rouge
      value: 47.6682
      verified: true
    - name: ROUGE-2
      type: rouge
      value: 23.3053
      verified: true
    - name: ROUGE-L
      type: rouge
      value: 39.7678
      verified: true
    - name: ROUGE-LSUM
      type: rouge
      value: 43.259
      verified: true
    - name: loss
      type: loss
      value: 2.372586965560913
      verified: true
    - name: gen_len
      type: gen_len
      value: 17.4237
      verified: true
---


# flan-t5-large-stacked-samsum-1024

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the `stacked-summaries/stacked-samsum-1024` dataset.

It achieves the following results on the evaluation set:
- Loss: 2.1311
- Rouge1: 58.1114
- Rouge2: 29.339
- Rougel: 44.7611
- Rougelsum: 54.2823
- Gen Len: 122.364

## Model description

More information needed

## Intended uses & limitations

- max input/output is 1024 tokens
- this is mostly a test because `samsum` is not exactly the best dataset for general purpose summarization

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0006
- train_batch_size: 4
- eval_batch_size: 2
- seed: 2760
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 32
- total_train_batch_size: 256
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.02
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.1734        | 1.0   | 115  | 1.8751          | 57.9286 | 29.2743 | 44.7181 | 54.2295   | 122.123 |
| 0.1098        | 2.0   | 230  | 2.1311          | 58.1114 | 29.339  | 44.7611 | 54.2823   | 122.364 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.1