my_wikilingua_model_bart1

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.9696
• Rouge1: 0.3492
• Rouge2: 0.1355
• Rougel: 0.2783
• Rougelsum: 0.2786
• Gen Len: 26.975

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: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 4
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
3.65	1.0	800	3.0221	0.3017	0.1156	0.2432	0.2433	22.085
2.7107	2.0	1600	2.9341	0.3424	0.1313	0.2686	0.2689	25.65
2.3206	3.0	2400	2.9409	0.3522	0.1348	0.2779	0.2779	27.8725
2.0027	4.0	3200	2.9696	0.3492	0.1355	0.2783	0.2786	26.975

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.0+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3