bart-base-xsum-rouge-3-loss-differentiable-100-cnt-supervised-sequential

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bart-base-xsum-rouge-3-loss-differentiable-100-cnt-supervised-sequential

This model is a fine-tuned version of taiypeo/bart-base-xsum-sentence-paraphrased-100-cnt-supervised-basic on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 2.2085
• Rouge1: 0.3308
• Rouge2: 0.1167
• Rougel: 0.26
• Rougelsum: 0.2601

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: 1e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 5

Training results

Framework versions

• Transformers 4.57.3
• Pytorch 2.9.1+cu128
• Datasets 3.6.0
• Tokenizers 0.22.1