mbart_cnn_summarization_10K_8ep_2e-5_batch_8_warmup_saved_best_3.03

• Loss: 3.1121
• Rouge1: 41.137
• Rouge2: 18.8121
• Rougel: 28.7393
• Rougelsum: 28.7414
• Gen Len: 73.508

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• 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: linear
• lr_scheduler_warmup_steps: 0.05
• num_epochs: 15
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.1

Training results

Framework versions

• Transformers 5.0.0
• Pytorch 2.10.0+cu128
• Datasets 4.6.1
• Tokenizers 0.22.2