roberta-base-bne-sentiment-analysis

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

• Loss: 0.3186
• Accuracy: 0.9194
• Precision: 0.9411
• Recall: 0.9671
• F1: 0.9539

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.2228	1.0	2500	0.2744	0.9184	0.9345	0.9738	0.9537
0.1653	2.0	5000	0.3186	0.9194	0.9411	0.9671	0.9539

Framework versions

• Transformers 4.52.3
• Pytorch 2.6.0+cu124
• Datasets 2.14.4
• Tokenizers 0.21.1