roberta-large-finetuned-augmentation-LUNAR-TAPT-macro

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

• Loss: 0.2832
• F1: 0.8635
• Roc Auc: 0.8937
• Accuracy: 0.7150

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: cosine
• lr_scheduler_warmup_steps: 100
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.2744	1.0	421	0.2710	0.7932	0.8326	0.5754
0.2287	2.0	842	0.2281	0.8454	0.8815	0.6758
0.1678	3.0	1263	0.2293	0.8563	0.8879	0.7049
0.1287	4.0	1684	0.2491	0.8619	0.8918	0.7126
0.1298	5.0	2105	0.2591	0.8633	0.8936	0.7173
0.0788	6.0	2526	0.2703	0.8612	0.8914	0.7138
0.0883	7.0	2947	0.2679	0.8605	0.8905	0.7203
0.0821	8.0	3368	0.2832	0.8635	0.8937	0.7150
0.0739	9.0	3789	0.2998	0.8601	0.8963	0.7156
0.0538	10.0	4210	0.2951	0.8615	0.8957	0.7167
0.0466	11.0	4631	0.2999	0.8626	0.8976	0.7126
0.0657	12.0	5052	0.3060	0.8608	0.8976	0.7203

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0