1d8781fc0b8941a50ad21c1ed922daad

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

• Loss: 0.6231
• Data Size: 0.25
• Epoch Runtime: 7.6889
• 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	0.7795	0	1.4399	0.3115	0.2375	0.3105	0.0	0.3115	0.3115
No log	1	267	0.6897	0.0078	2.2088	0.6875	0.4104	0.6875	0.0	0.6875	0.6875
No log	2	534	0.6193	0.0156	2.2301	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	3	801	0.6253	0.0312	2.8799	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	4	1068	0.6234	0.0625	3.6736	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.0382	5	1335	0.6267	0.125	5.0179	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.612	6	1602	0.6231	0.25	7.6889	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