|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: bert-base-cased-DreamBank |
|
results: [] |
|
widget: |
|
- text: >- |
|
I dreamed that Hannah and Sue and I travelled back in time to meet her |
|
parents. Weird. |
|
pipeline_tag: text-classification |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# bert-base-cased-DreamBank |
|
|
|
This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2697 |
|
- F1: 0.8335 |
|
- Roc Auc: 0.8761 |
|
- Accuracy: 0.6703 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
|
| No log | 1.0 | 185 | 0.5983 | 0.0330 | 0.5064 | 0.0162 | |
|
| No log | 2.0 | 370 | 0.3939 | 0.6104 | 0.7317 | 0.4649 | |
|
| 0.4638 | 3.0 | 555 | 0.3227 | 0.7572 | 0.8154 | 0.5568 | |
|
| 0.4638 | 4.0 | 740 | 0.2852 | 0.7902 | 0.8412 | 0.5784 | |
|
| 0.4638 | 5.0 | 925 | 0.2720 | 0.7982 | 0.8382 | 0.6270 | |
|
| 0.1877 | 6.0 | 1110 | 0.2795 | 0.8144 | 0.8619 | 0.6541 | |
|
| 0.1877 | 7.0 | 1295 | 0.2575 | 0.8147 | 0.8568 | 0.6541 | |
|
| 0.1877 | 8.0 | 1480 | 0.2556 | 0.8204 | 0.8630 | 0.6595 | |
|
| 0.0952 | 9.0 | 1665 | 0.2668 | 0.8321 | 0.8764 | 0.6703 | |
|
| 0.0952 | 10.0 | 1850 | 0.2697 | 0.8335 | 0.8761 | 0.6703 | |
|
|
|
|
|
### 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} |
|
} |
|
``` |
