---
license: apache-2.0
base_model: google/flan-t5-large
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: flan-t5-large-samsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: test
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 49.1053
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# flan-t5-large-samsum

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2066
- Rouge1: 49.1053
- Rouge2: 25.4565
- Rougel: 41.9146
- Rougelsum: 45.3592
- Gen Len: 17.1380

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.1847        | 1.0   | 1844 | 1.2066          | 49.1053 | 25.4565 | 41.9146 | 45.3592   | 17.1380 |
| 1.0533        | 2.0   | 3688 | 1.2126          | 49.5421 | 26.1526 | 42.1131 | 45.5735   | 17.2564 |
| 0.9521        | 3.0   | 5532 | 1.2315          | 49.7252 | 26.1855 | 42.2726 | 45.747    | 17.3358 |
| 0.8746        | 4.0   | 7376 | 1.2510          | 49.4306 | 25.9048 | 41.9821 | 45.4322   | 17.4750 |
| 0.8334        | 5.0   | 9220 | 1.2631          | 49.4852 | 25.9416 | 42.0469 | 45.5014   | 17.3944 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1