transformers safetensors t5 text2text-generation generated_from_trainer base_model:google/flan-t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: QA-flan-t5-small
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# QA-flan-t5-small

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4875
- Rouge1: 0.6697
- Rouge2: 0.4916
- Rougel: 0.6692
- Rougelsum: 0.6694

## 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: 6

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|
| 0.7836        | 1.0   | 30468  | 0.5139          | 0.6377 | 0.4690 | 0.6373 | 0.6371    |
| 0.6817        | 2.0   | 60936  | 0.4990          | 0.6428 | 0.4674 | 0.6421 | 0.6422    |
| 0.6913        | 3.0   | 91404  | 0.4999          | 0.6504 | 0.4706 | 0.6496 | 0.6496    |
| 0.5839        | 4.0   | 121872 | 0.4808          | 0.6680 | 0.4918 | 0.6675 | 0.6676    |
| 0.58          | 5.0   | 152340 | 0.4871          | 0.6702 | 0.4919 | 0.6697 | 0.6698    |
| 0.5921        | 6.0   | 182808 | 0.4875          | 0.6697 | 0.4916 | 0.6692 | 0.6694    |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
