This model is a fine-tuned version of BSC-TeMU/roberta-base-bne on the multilingual-sentiments dataset. It achieves the following results on the evaluation set:

Loss: 0.7635
Accuracy: 0.7222

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
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
0.6192	1.0	115	0.6712	0.7099
0.217	2.0	230	0.7635	0.7222

Framework versions

Transformers 4.35.0
Pytorch 1.13.1+cu117
Datasets 2.14.6
Tokenizers 0.14.1

juliowaissman/roberta-base-bne-finetuned-multi-sentiment

roberta-base-bne-finetuned-multi-sentiment

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

juliowaissman/
roberta-base-bne-finetuned-multi-sentiment