f78d21c7edd47526afd4354d775eb629

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

• Loss: 1.1034
• Data Size: 0.125
• Epoch Runtime: 249.5777
• Accuracy: 0.3545
• F1 Macro: 0.1745
• Rouge1: 0.3544
• Rouge2: 0.0
• Rougel: 0.3545
• Rougelsum: 0.3543

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	1.1689	0	13.5525	0.3182	0.1624	0.3183	0.0	0.3181	0.3184
1.1208	1	12271	1.0972	0.0078	29.6772	0.3545	0.1745	0.3544	0.0	0.3545	0.3543
1.1155	2	24542	1.0983	0.0156	44.5412	0.3545	0.1745	0.3544	0.0	0.3545	0.3543
1.1048	3	36813	1.1006	0.0312	74.6123	0.3182	0.1609	0.3184	0.0	0.3182	0.3183
1.1128	4	49084	1.0979	0.0625	132.8406	0.3545	0.1745	0.3544	0.0	0.3545	0.3543
1.1119	5	61355	1.1034	0.125	249.5777	0.3545	0.1745	0.3544	0.0	0.3545	0.3543

Framework versions

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