51bcc7f84f28c87d9ff2b98f9418cc6f

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

• Loss: 0.6684
• Data Size: 0.125
• Epoch Runtime: 269.8816
• Accuracy: 0.6320
• F1 Macro: 0.3872
• Rouge1: 0.6318
• Rouge2: 0.0
• Rougel: 0.6319
• Rougelsum: 0.6317

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	0.7256	0	53.2630	0.3761	0.2898	0.3762	0.0	0.3761	0.3764
0.6795	1	11370	0.6587	0.0078	68.0249	0.6320	0.3872	0.6318	0.0	0.6319	0.6317
0.6684	2	22740	0.6589	0.0156	82.0631	0.6320	0.3872	0.6318	0.0	0.6319	0.6317
0.6562	3	34110	0.6604	0.0312	109.8392	0.6320	0.3872	0.6318	0.0	0.6319	0.6317
0.6674	4	45480	0.6624	0.0625	162.6997	0.6320	0.3872	0.6318	0.0	0.6319	0.6317
0.6687	5	56850	0.6684	0.125	269.8816	0.6320	0.3872	0.6318	0.0	0.6319	0.6317

Framework versions

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