results

This model is a fine-tuned version of pietrocagnasso/bart-paper-titles on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 1.8363
• eval_rouge1: 0.2932
• eval_rouge2: 0.1496
• eval_rougeL: 0.2387
• eval_rougeLsum: 0.2387
• eval_gen_len: 59.7278
• eval_runtime: 6791.8637
• eval_samples_per_second: 3.975
• eval_steps_per_second: 0.124
• epoch: 2.0
• step: 3375

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Framework versions

• Transformers 4.44.0
• Pytorch 2.4.0
• Datasets 2.21.0
• Tokenizers 0.19.1