mbart-dutch-summarization

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model

This model is a fine-tuned version of ml6team/mbart-large-cc25-cnn-dailymail-nl-finetune on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 3.2703
• Rouge1: 39.0974
• Rouge2: 16.3611
• Rougel: 32.9845
• Rougelsum: 33.4518
• Gen Len: 23.9853

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: 2e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 3.0
• label_smoothing_factor: 0.1

Training results

Framework versions

• Transformers 4.56.2
• Pytorch 2.8.0+cu129
• Datasets 4.1.0
• Tokenizers 0.22.1