mbart-large-50_Nepali_News_Summarization_QLoRA_8bit

This model is a fine-tuned version of facebook/mbart-large-50 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.3724
• Rouge-1 R: 0.3809
• Rouge-1 P: 0.3877
• Rouge-1 F: 0.3745
• Rouge-2 R: 0.2144
• Rouge-2 P: 0.2176
• Rouge-2 F: 0.2093
• Rouge-l R: 0.3702
• Rouge-l P: 0.3766
• Rouge-l F: 0.364
• Gen Len: 14.0747

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: 0.0005
• train_batch_size: 5
• eval_batch_size: 5
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge-1 R	Rouge-1 P	Rouge-1 F	Rouge-2 R	Rouge-2 P	Rouge-2 F	Rouge-l R	Rouge-l P	Rouge-l F	Gen Len
1.5604	1.0	10191	1.5916	0.3605	0.3694	0.3536	0.1948	0.2008	0.19	0.3501	0.3586	0.3433	14.7262
1.5482	2.0	20382	1.3992	0.3673	0.3879	0.3672	0.2034	0.2149	0.202	0.3577	0.3775	0.3575	13.7928
1.2397	3.0	30573	1.3724	0.3809	0.3877	0.3745	0.2144	0.2176	0.2093	0.3702	0.3766	0.364	14.0747

Framework versions

• PEFT 0.11.1
• Transformers 4.42.3
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1