---
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: 0.2967
---

<!-- 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: 3.1243
- Rouge1: 0.2967
- Rouge2: 0.1277
- Rougel: 0.2457
- Rougelsum: 0.2602

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.9845        | 1.0   | 63   | 3.2358          | 0.288  | 0.1219 | 0.238  | 0.2522    |
| 2.7469        | 2.0   | 126  | 3.1815          | 0.2922 | 0.1251 | 0.2415 | 0.2562    |
| 2.7032        | 3.0   | 189  | 3.1564          | 0.2991 | 0.1303 | 0.2474 | 0.2619    |
| 2.6479        | 4.0   | 252  | 3.1354          | 0.2973 | 0.1282 | 0.2457 | 0.2608    |
| 2.6303        | 5.0   | 315  | 3.1297          | 0.2964 | 0.1272 | 0.2451 | 0.2598    |
| 2.6115        | 6.0   | 378  | 3.1243          | 0.2967 | 0.1277 | 0.2457 | 0.2602    |
| 2.5704        | 7.0   | 441  | 3.1264          | 0.2967 | 0.127  | 0.2453 | 0.26      |
| 2.6028        | 8.0   | 504  | 3.1252          | 0.2971 | 0.1275 | 0.2456 | 0.2604    |


### Framework versions

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