transformers tensorboard safetensors t5 text2text-generation summarization generated_from_trainer dataset:scientific_papers base_model:google/flan-t5-small base_model:finetune:google/flan-t5-small license:apache-2.0 model-index autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: google/flan-t5-small
datasets:
- scientific_papers
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: flan-t5-small-finetuned-scientific-articles
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: scientific_papers
      type: scientific_papers
      config: pubmed
      split: train
      args: pubmed
    metrics:
    - type: rouge
      value: 8.0297
      name: Rouge1
---

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# flan-t5-small-finetuned-scientific-articles

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the scientific_papers dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6792
- Rouge1: 8.0297
- Rouge2: 2.5421
- Rougel: 6.6908
- Rougelsum: 7.3431

## 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: 5.6e-05
- train_batch_size: 9
- eval_batch_size: 9
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.0943        | 1.0   | 56   | 2.8262          | 3.9456 | 1.1211 | 3.3527 | 3.6682    |
| 3.0216        | 2.0   | 112  | 2.7682          | 6.0659 | 1.6822 | 5.2499 | 5.7102    |
| 2.9495        | 3.0   | 168  | 2.7316          | 7.4704 | 2.4232 | 6.2443 | 6.913     |
| 2.9057        | 4.0   | 224  | 2.7050          | 7.8789 | 2.6559 | 6.5559 | 7.1858    |
| 2.8622        | 5.0   | 280  | 2.6792          | 8.0297 | 2.5421 | 6.6908 | 7.3431    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
