sentence_eval1

This model is a fine-tuned version of roberta-large-mnli on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.4766
• Precision: {'precision': 0.863681451041519}
• Recall: {'recall': 0.8702170188463735}
• F1: {'f1': 0.8669369177156675}
• Acc: {'accuracy': 0.8073120494335736}

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: 48
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Acc
0.437	1.0	1771	0.4753	{'precision': 0.9119431443924424}	{'recall': 0.7511422044545973}	{'f1': 0.8237688874970641}	{'accuracy': 0.7681771369721936}
0.367	2.0	3542	0.4342	{'precision': 0.8658256880733946}	{'recall': 0.8623643632210166}	{'f1': 0.8640915593705294}	{'accuracy': 0.8043254376930999}
0.2915	3.0	5313	0.4766	{'precision': 0.863681451041519}	{'recall': 0.8702170188463735}	{'f1': 0.8669369177156675}	{'accuracy': 0.8073120494335736}

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.7.1
• Tokenizers 0.13.2