---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-finetuned-scitldr
  results: []
---

<!-- 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. -->

# t5-base-finetuned-scitldr

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1055
- Rouge1: 23.6222
- Rouge2: 10.2432
- Rougel: 19.702
- Rougelsum: 20.9458
- Gen Len: 18.979

## 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: 4e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.4272        | 0.1   | 100  | 3.1951          | 23.0447 | 9.7818  | 19.0676 | 20.1677   | 18.9532 |
| 2.0362        | 0.2   | 200  | 3.1715          | 23.5443 | 10.1156 | 19.5788 | 20.6995   | 18.9483 |
| 2.188         | 0.3   | 300  | 3.1067          | 24.2387 | 10.3059 | 20.0964 | 21.2592   | 18.9338 |
| 2.0312        | 0.4   | 400  | 3.1092          | 23.3168 | 10.1308 | 19.4275 | 20.611    | 18.9742 |
| 2.012         | 0.5   | 500  | 3.1189          | 23.6989 | 10.3005 | 19.7634 | 20.9462   | 18.9758 |
| 2.0581        | 0.6   | 600  | 3.1191          | 23.6818 | 10.2636 | 19.7953 | 20.9935   | 18.9774 |
| 2.0067        | 0.7   | 700  | 3.1297          | 23.8476 | 10.5139 | 19.9696 | 21.1594   | 18.9774 |
| 2.0049        | 0.8   | 800  | 3.1150          | 23.6929 | 10.3243 | 19.7895 | 21.0455   | 18.979  |
| 2.1839        | 0.9   | 900  | 3.1055          | 23.6222 | 10.2432 | 19.702  | 20.9458   | 18.979  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0