metadata

license: apache-2.0
base_model: BSC-TeMU/roberta-base-bne
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
model-index:
  - name: roberta-base-bne-finetuned-detests-wandb24
    results: []

roberta-base-bne-finetuned-detests-wandb24

This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.4065
Accuracy: 0.8527
F1-score: 0.7826
Precision: 0.7945
Recall: 0.7727
Auc: 0.7727

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: 5e-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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1-score	Precision	Recall	Auc
0.3296	1.0	77	0.3456	0.8543	0.7671	0.8142	0.7408	0.7408
0.1555	2.0	154	0.4065	0.8527	0.7826	0.7945	0.7727	0.7727

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1