3ee4e536378ff7ac1ed911ddf7b352b5

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

• Loss: 0.6307
• Data Size: 1.0
• Epoch Runtime: 42.1433
• Accuracy: 0.6885
• F1 Macro: 0.4078
• Rouge1: 0.6895
• Rouge2: 0.0
• Rougel: 0.6885
• Rougelsum: 0.6885

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	0.8659	0	1.9539	0.3115	0.2375	0.3105	0.0	0.3115	0.3115
No log	1	267	0.6213	0.0078	3.4720	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	2	534	0.6386	0.0156	3.0432	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	3	801	0.7067	0.0312	4.0733	0.3115	0.2375	0.3105	0.0	0.3115	0.3115
No log	4	1068	0.6201	0.0625	5.8955	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.0382	5	1335	0.6205	0.125	8.4156	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6114	6	1602	0.6204	0.25	13.4348	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6255	7	1869	0.6261	0.5	22.5591	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.6073	8.0	2136	0.6307	1.0	42.1433	0.6885	0.4078	0.6895	0.0	0.6885	0.6885

Framework versions

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