roberta_classification

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

• Loss: 1.2731
• Accuracy: {'accuracy': 0.8465909090909091}
• F1: {'f1': 0.8396445042099528}

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: 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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	263	1.1741	{'accuracy': 0.6363636363636364}	{'f1': 0.6202787331893512}
1.181	2.0	526	0.9322	{'accuracy': 0.7386363636363636}	{'f1': 0.7177199655598837}
1.181	3.0	789	0.7835	{'accuracy': 0.7727272727272727}	{'f1': 0.7657783584890875}
0.3689	4.0	1052	0.8597	{'accuracy': 0.7727272727272727}	{'f1': 0.768360357103512}
0.3689	5.0	1315	0.7560	{'accuracy': 0.8125}	{'f1': 0.8031513875852524}
0.165	6.0	1578	0.7579	{'accuracy': 0.8200757575757576}	{'f1': 0.8142845258630059}
0.165	7.0	1841	0.8900	{'accuracy': 0.8352272727272727}	{'f1': 0.8316422201059607}
0.0778	8.0	2104	0.9315	{'accuracy': 0.8295454545454546}	{'f1': 0.825285136658407}
0.0778	9.0	2367	1.1370	{'accuracy': 0.8181818181818182}	{'f1': 0.8091288762824846}
0.0335	10.0	2630	1.0799	{'accuracy': 0.8465909090909091}	{'f1': 0.841700330957688}
0.0335	11.0	2893	1.2487	{'accuracy': 0.8314393939393939}	{'f1': 0.8269815181159639}
0.0162	12.0	3156	1.2194	{'accuracy': 0.8295454545454546}	{'f1': 0.8243565671691487}
0.0162	13.0	3419	1.2592	{'accuracy': 0.8333333333333334}	{'f1': 0.8312612314115424}
0.0073	14.0	3682	1.2885	{'accuracy': 0.8257575757575758}	{'f1': 0.8198413592956925}
0.0073	15.0	3945	1.2133	{'accuracy': 0.8352272727272727}	{'f1': 0.8291568008253063}
0.0046	16.0	4208	1.2625	{'accuracy': 0.8409090909090909}	{'f1': 0.8343252944129244}
0.0046	17.0	4471	1.2498	{'accuracy': 0.8409090909090909}	{'f1': 0.8356461395476784}
0.0032	18.0	4734	1.3041	{'accuracy': 0.8390151515151515}	{'f1': 0.8307896138032654}
0.0032	19.0	4997	1.2544	{'accuracy': 0.8446969696969697}	{'f1': 0.83889081905153}
0.0022	20.0	5260	1.2731	{'accuracy': 0.8465909090909091}	{'f1': 0.8396445042099528}

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1