8a10bea29314b726ae2c71759707b07d

This model is a fine-tuned version of FacebookAI/xlm-roberta-large-finetuned-conll02-spanish on the nyu-mll/glue [cola] dataset. It achieves the following results on the evaluation set:

• Loss: 0.6629
• Data Size: 0.125
• Epoch Runtime: 10.0097
• 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	0.6248	0	2.0551	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	1	267	0.6253	0.0078	3.6877	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	2	534	0.6611	0.0156	3.4569	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
No log	3	801	0.7051	0.0312	4.8848	0.5361	0.4989	0.5352	0.0	0.5356	0.5361
No log	4	1068	0.6262	0.0625	6.8126	0.6885	0.4078	0.6895	0.0	0.6885	0.6885
0.0398	5	1335	0.6629	0.125	10.0097	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