llama2-7bb-tweet-summarization-gradnorm-0.3

This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the dialogstudio dataset. It achieves the following results on the evaluation set:

• Loss: 2.8160
• Rouge Scores: {'rouge1': 93.719779910895, 'rouge2': 78.0799701185797, 'rougeL': 64.91384075272471, 'rougeLsum': 93.71249369436103}
• Bleu Scores: [0.9468715981421053, 0.9340571158071639, 0.906767913949756, 0.8753561378232885]
• Gen Len: 463.0182

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: 0.0001
• train_batch_size: 4
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 7
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge Scores	Bleu Scores	Gen Len
1.9246	1.0	220	1.8384	{'rouge1': 92.78080137059182, 'rouge2': 78.71532643138437, 'rougeL': 68.0616149947273, 'rougeLsum': 92.78702835703021}	[0.9079275318266272, 0.8970741286020552, 0.8736002135507472, 0.8466150307526832]	463.0182
1.6564	2.0	440	1.8335	{'rouge1': 93.62527163754612, 'rouge2': 79.14899366889107, 'rougeL': 68.02122989340602, 'rougeLsum': 93.62676386700348}	[0.9282164809556785, 0.9171615801879893, 0.892709310950969, 0.8645188775345913]	463.0182
1.3403	3.0	660	1.9481	{'rouge1': 93.70688850262614, 'rouge2': 78.96026100012381, 'rougeL': 67.37638965440908, 'rougeLsum': 93.70399692691778}	[0.9342903619020663, 0.9225682522334384, 0.8972845918789121, 0.8681853449069523]	463.0182
0.9984	4.0	880	2.1537	{'rouge1': 93.77800041953847, 'rouge2': 78.72204799373465, 'rougeL': 66.56763131340682, 'rougeLsum': 93.77100407824561}	[0.9425931953005738, 0.9302863494509406, 0.9040669212466305, 0.8739193334758137]	463.0182
0.7	5.0	1100	2.3692	{'rouge1': 93.74639046979189, 'rouge2': 78.51569240275262, 'rougeL': 65.93032986525995, 'rougeLsum': 93.73745084400457}	[0.9440175755443134, 0.93171453625075, 0.9052208696375351, 0.8747208115562404]	463.0182
0.4947	6.0	1320	2.6590	{'rouge1': 93.75661844384149, 'rouge2': 78.18805763398609, 'rougeL': 65.29243896759789, 'rougeLsum': 93.75034348574664}	[0.9470358425741272, 0.9342995624545122, 0.9070823690393129, 0.8757451333358709]	463.0182
0.3922	7.0	1540	2.8160	{'rouge1': 93.719779910895, 'rouge2': 78.0799701185797, 'rougeL': 64.91384075272471, 'rougeLsum': 93.71249369436103}	[0.9468715981421053, 0.9340571158071639, 0.906767913949756, 0.8753561378232885]	463.0182

Framework versions

• PEFT 0.8.2.dev0
• Transformers 4.38.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.16.2.dev0
• Tokenizers 0.15.1