4f89c1aa4e9e67725a6de07a0e57cf65

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

• Loss: 1.1050
• Data Size: 0.25
• Epoch Runtime: 477.3935
• Accuracy: 0.3182
• F1 Macro: 0.1609
• Rouge1: 0.3184
• Rouge2: 0.0
• Rougel: 0.3182
• Rougelsum: 0.3183

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	1.1493	0	13.9483	0.3212	0.1806	0.3213	0.0	0.3208	0.3212
1.1202	1	12271	1.0984	0.0078	28.8975	0.3182	0.1609	0.3184	0.0	0.3182	0.3183
1.1157	2	24542	1.0978	0.0156	43.6521	0.3545	0.1745	0.3544	0.0	0.3545	0.3543
1.1071	3	36813	1.1005	0.0312	73.9771	0.3273	0.1644	0.3273	0.0	0.3275	0.3277
1.1139	4	49084	1.0979	0.0625	132.4745	0.3545	0.1745	0.3544	0.0	0.3545	0.3543
1.1142	5	61355	1.1020	0.125	248.5493	0.3545	0.1745	0.3544	0.0	0.3545	0.3543
1.1043	6	73626	1.1050	0.25	477.3935	0.3182	0.1609	0.3184	0.0	0.3182	0.3183

Framework versions

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