npl-transformes-crivera

This model is a fine-tuned version of distilroberta-base on the glue and the mrpc datasets. It achieves the following results on the evaluation set:

• Loss: 0.4284
• Accuracy: 0.8407
• F1: 0.8776

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: 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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5382	1.0893	500	0.4284	0.8407	0.8776
0.3837	2.1786	1000	0.7435	0.8382	0.8893
0.2372	3.2680	1500	0.8933	0.8235	0.88

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cpu
• Datasets 3.1.0
• Tokenizers 0.20.3