roberta-Reflections-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current

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: 0.2525
• Accuracy: 0.8947
• Precision: 0.5424
• Recall: 0.3678
• F1: 0.4384

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: 3.322508414488167e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.32	1.0	61	0.1403	0.8883	0.0	0.0	0.0
0.2689	2.0	122	0.1174	0.8883	0.0	0.0	0.0
0.2466	3.0	183	0.1255	0.8883	0.0	0.0	0.0
0.2297	4.0	244	0.0992	0.8883	0.0	0.0	0.0
0.2138	5.0	305	0.1326	0.8986	0.5690	0.3793	0.4552
0.1877	6.0	366	0.1163	0.8909	0.5179	0.3333	0.4056
0.1558	7.0	427	0.1209	0.8947	0.5397	0.3908	0.4533
0.135	8.0	488	0.1446	0.8896	0.5056	0.5172	0.5114
0.1208	9.0	549	0.1435	0.8986	0.5455	0.5517	0.5486
0.1212	10.0	610	0.2261	0.8665	0.4309	0.6092	0.5048
0.1011	11.0	671	0.1425	0.8973	0.5714	0.3218	0.4118
0.0918	12.0	732	0.2365	0.8832	0.4811	0.5862	0.5285
0.0892	13.0	793	0.1622	0.8935	0.525	0.4828	0.5030
0.0593	14.0	854	0.1927	0.8922	0.5273	0.3333	0.4085
0.0552	15.0	915	0.3540	0.8819	0.4762	0.5747	0.5208
0.0523	16.0	976	0.2782	0.8909	0.5119	0.4943	0.5029
0.0481	17.0	1037	0.2596	0.8922	0.5195	0.4598	0.4878
0.0435	18.0	1098	0.2729	0.8947	0.5333	0.4598	0.4938
0.0326	19.0	1159	0.2382	0.8935	0.5385	0.3218	0.4029
0.0418	20.0	1220	0.2525	0.8947	0.5424	0.3678	0.4384

Framework versions

• Transformers 4.48.3
• Pytorch 2.5.1+cu124
• Datasets 2.21.0
• Tokenizers 0.21.0