---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-DreamBank-Generation-Emot-EmotNn
  results: []
language:
- en
widget:
- text: "I had a dream that Ben was in Costa Rica. I was really nervous about something, and he tried to make me feel better. Then Delia was in the library and had turned all the lights off. I was scared to lose my books since I had a paper due the next day."
---

<!-- 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-DreamBank-Generation-Emot-EmotNn

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3559
- Rouge1: 0.8119
- Rouge2: 0.2070
- Rougel: 0.8102
- Rougelsum: 0.8115

## 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: 0.0002
- 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 1.0   | 24   | 0.5128          | 0.5154 | 0.0562 | 0.5072 | 0.5086    |
| No log        | 2.0   | 48   | 0.3782          | 0.7132 | 0.0145 | 0.7127 | 0.7159    |
| No log        | 3.0   | 72   | 0.3387          | 0.7872 | 0.1712 | 0.7745 | 0.7756    |
| No log        | 4.0   | 96   | 0.3221          | 0.7804 | 0.1598 | 0.7754 | 0.7777    |
| No log        | 5.0   | 120  | 0.3669          | 0.7453 | 0.1330 | 0.7403 | 0.7414    |
| No log        | 6.0   | 144  | 0.3559          | 0.8119 | 0.2070 | 0.8102 | 0.8115    |
| No log        | 7.0   | 168  | 0.3559          | 0.8047 | 0.1895 | 0.8036 | 0.8047    |
| No log        | 8.0   | 192  | 0.3808          | 0.7967 | 0.1925 | 0.7934 | 0.7949    |
| No log        | 9.0   | 216  | 0.3899          | 0.8047 | 0.2127 | 0.8030 | 0.8040    |
| No log        | 10.0  | 240  | 0.3991          | 0.8096 | 0.2247 | 0.8068 | 0.8074    |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.5.1
- Tokenizers 0.12.1

### Cite 
If you use the model, please cite the pre-print.
```bibtex
@misc{https://doi.org/10.48550/arxiv.2302.14828,
  doi = {10.48550/ARXIV.2302.14828},
  url = {https://arxiv.org/abs/2302.14828},
  author = {Bertolini, Lorenzo and Elce, Valentina and Michalak, Adriana and Bernardi, Giulio and Weeds, Julie},
  keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
  title = {Automatic Scoring of Dream Reports' Emotional Content with Large Language Models},
  publisher = {arXiv},
  year = {2023},
  copyright = {Creative Commons Attribution 4.0 International}
}
```