Bart-base-v2

This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: nan

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: 5e-05
• train_batch_size: 3
• eval_batch_size: 3
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 12
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss
985982.912	0.24	250	nan
0.0	0.48	500	nan
0.0	0.72	750	nan
0.0	0.96	1000	nan
0.0	1.2	1250	nan
0.0	1.44	1500	nan
0.0	1.69	1750	nan
0.0	1.93	2000	nan
0.0	2.17	2250	nan
0.0	2.41	2500	nan
0.0	2.65	2750	nan
0.0	2.89	3000	nan
0.0	3.13	3250	nan
0.0	3.37	3500	nan
0.0	3.61	3750	nan
0.0	3.85	4000	nan
0.0	4.09	4250	nan
0.0	4.33	4500	nan
0.0	4.57	4750	nan
0.0	4.81	5000	nan
0.0	5.06	5250	nan
0.0	5.3	5500	nan
0.0	5.54	5750	nan
0.0	5.78	6000	nan

Framework versions

• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.19.1
• Tokenizers 0.15.2