6c6b0e01a0856a4e21e4c50e08c88332

This model is a fine-tuned version of FacebookAI/xlm-roberta-large-finetuned-conll03-english on the nyu-mll/glue [wnli] dataset. It achieves the following results on the evaluation set:

• Loss: 0.6862
• Data Size: 1.0
• Epoch Runtime: 8.7474
• Accuracy: 0.5625
• F1 Macro: 0.36
• Rouge1: 0.5625
• Rouge2: 0.0
• Rougel: 0.5625
• Rougelsum: 0.5625

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
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: constant
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Data Size	Epoch Runtime	Accuracy	F1 Macro	Rouge1	Rouge2	Rougel	Rougelsum
No log	0	0	0.7119	0	0.7446	0.4375	0.3043	0.4375	0.0	0.4375	0.4375
No log	1	19	0.6964	0.0078	1.1185	0.5625	0.36	0.5625	0.0	0.5625	0.5625
No log	2	38	0.7413	0.0156	2.1725	0.4375	0.3043	0.4375	0.0	0.4375	0.4375
No log	3	57	0.6948	0.0312	2.7221	0.4688	0.3637	0.4688	0.0	0.4688	0.4688
No log	4	76	0.6875	0.0625	3.4576	0.5625	0.36	0.5625	0.0	0.5625	0.5625
No log	5	95	0.6856	0.125	4.0438	0.5625	0.36	0.5625	0.0	0.5625	0.5625
0.083	6	114	0.6912	0.25	4.7979	0.5	0.4182	0.5	0.0	0.5	0.5
0.083	7	133	0.6894	0.5	6.2060	0.5625	0.36	0.5625	0.0	0.5625	0.5625
0.5246	8.0	152	0.6873	1.0	8.7311	0.5625	0.36	0.5625	0.0	0.5625	0.5625
0.5246	9.0	171	0.6854	1.0	9.2789	0.5625	0.36	0.5625	0.0	0.5625	0.5625
0.5246	10.0	190	0.7159	1.0	6.9896	0.4375	0.3043	0.4375	0.0	0.4375	0.4375
0.7048	11.0	209	0.7186	1.0	7.5326	0.4375	0.3043	0.4375	0.0	0.4375	0.4375
0.7048	12.0	228	0.6844	1.0	7.2992	0.5625	0.36	0.5625	0.0	0.5625	0.5625
0.7048	13.0	247	0.6892	1.0	7.6236	0.5625	0.36	0.5625	0.0	0.5625	0.5625
0.7065	14.0	266	0.6862	1.0	7.8478	0.5625	0.36	0.5625	0.0	0.5625	0.5625
0.7065	15.0	285	0.7049	1.0	8.6253	0.4375	0.3043	0.4375	0.0	0.4375	0.4375
0.7047	16.0	304	0.6862	1.0	8.7474	0.5625	0.36	0.5625	0.0	0.5625	0.5625

Framework versions

• Transformers 4.57.0
• Pytorch 2.8.0+cu128
• Datasets 4.3.0
• Tokenizers 0.22.1