---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- scitldr
metrics:
- rouge
model-index:
- name: paper-summary
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: scitldr
      type: scitldr
      config: Abstract
      split: train
      args: Abstract
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.3484
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# paper-summary

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the scitldr dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8631
- Rouge1: 0.3484
- Rouge2: 0.1596
- Rougel: 0.2971
- Rougelsum: 0.3047

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 3.0545        | 1.0   | 63   | 2.9939          | 0.3387 | 0.1538 | 0.2887 | 0.2957    |
| 2.7871        | 2.0   | 126  | 2.9360          | 0.3448 | 0.1577 | 0.2947 | 0.3019    |
| 2.7188        | 3.0   | 189  | 2.8977          | 0.3477 | 0.1585 | 0.2967 | 0.3035    |
| 2.6493        | 4.0   | 252  | 2.8837          | 0.3488 | 0.1597 | 0.2973 | 0.3046    |
| 2.6207        | 5.0   | 315  | 2.8690          | 0.3472 | 0.1566 | 0.2958 | 0.3033    |
| 2.5893        | 6.0   | 378  | 2.8668          | 0.3493 | 0.1592 | 0.2972 | 0.305     |
| 2.5494        | 7.0   | 441  | 2.8657          | 0.3486 | 0.1595 | 0.2976 | 0.3053    |
| 2.5554        | 8.0   | 504  | 2.8631          | 0.3484 | 0.1596 | 0.2971 | 0.3047    |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1