bn_sum_mt5_base

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mt5_large_riju_data

This model is a fine-tuned version of MahdiSUST/bn_sum on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.3531
• eval_rouge1: {'precision': 41.8541697896367, 'recall': 41.3654041539666, 'fmeasure': 40.98106539607074}
• eval_rougeL: {'precision': 39.824364163293794, 'recall': 39.31906760605605, 'fmeasure': 38.97108720823315}
• eval_runtime: 229.14
• eval_samples_per_second: 4.159
• eval_steps_per_second: 2.082
• epoch: 9

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: 5.6e-05
• train_batch_size: 9
• eval_batch_size: 9
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Framework versions

• Transformers 4.27.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2