bart_large_paraphrase_generator_en_de_v2

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bart_large_paraphrase_generator_en_de_v2

This model was trained from scratch on an unknown dataset.

Model description

More information needed

Intended uses & limitations

More information needed

{'eval_loss': 0.9200083613395691, 'eval_score': 49.97448884411352, 'eval_counts': [100712, 72963, 57055, 41578], 'eval_totals': [133837, 130839, 127841, 124843], 'eval_precisions': [75.24974409169363, 55.76548276889918, 44.6296571522438, 33.30423011302196], 'eval_bp': 1.0, 'eval_sys_len': 133837, 'eval_ref_len': 130883, 'eval_runtime': 138.6871, 'eval_samples_per_second': 21.617, 'eval_steps_per_second': 0.678}

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
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0

Framework versions

• Transformers 4.16.2
• Pytorch 1.11.0a0+bfe5ad2
• Datasets 1.18.3
• Tokenizers 0.11.0