llama2-7b-tweet-summarization

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: 2.8876
• Rouge Scores: {'rouge1': 71.60622394148149, 'rouge2': 59.01568798771897, 'rougeL': 48.52977346441143, 'rougeLsum': 71.51397796132038}
• Bleu Scores: [0.663980810175294, 0.6539436277190132, 0.6336458977384846, 0.6103966849577666]
• 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
1.9342	1.0	220	1.8650	{'rouge1': 81.3543855201909, 'rouge2': 68.33628607515259, 'rougeL': 58.82060003710821, 'rougeLsum': 81.31170089312123}	[0.7475269615217999, 0.7320503944473035, 0.7092142839754116, 0.6841937810377433]	463.0182
1.6847	2.0	440	1.8651	{'rouge1': 82.24291097248478, 'rouge2': 69.08611946264551, 'rougeL': 59.03857240450188, 'rougeLsum': 82.21842705467084}	[0.7506228265880205, 0.7370025856405312, 0.7147650770848061, 0.6900216562765312]	463.0182
1.3489	3.0	660	1.9777	{'rouge1': 74.8813002669941, 'rouge2': 62.506440459770204, 'rougeL': 52.7220886983953, 'rougeLsum': 74.84300846787131}	[0.6692327330499573, 0.6584063380227538, 0.6386775472556582, 0.6163741473600254]	463.0182
0.9474	4.0	880	2.1929	{'rouge1': 78.71628333472167, 'rouge2': 65.58881455717321, 'rougeL': 55.06014924478776, 'rougeLsum': 78.69638389807935}	[0.7102475447746652, 0.6987491736376487, 0.6776051942379059, 0.6536770956211561]	463.0182
0.6111	5.0	1100	2.4439	{'rouge1': 78.27895756478365, 'rouge2': 64.90905260843559, 'rougeL': 54.06285449810264, 'rougeLsum': 78.22155552696411}	[0.7449392180339443, 0.7329638020466664, 0.7106292329793894, 0.6852866075200218]	463.0182
0.3982	6.0	1320	2.7334	{'rouge1': 70.6225818335813, 'rouge2': 58.36070884299628, 'rougeL': 48.1310974990119, 'rougeLsum': 70.48308395430783}	[0.6525378114736703, 0.6423715222547518, 0.6226082916386746, 0.6000829162052789]	463.0182
0.3039	7.0	1540	2.8876	{'rouge1': 71.60622394148149, 'rouge2': 59.01568798771897, 'rougeL': 48.52977346441143, 'rougeLsum': 71.51397796132038}	[0.663980810175294, 0.6539436277190132, 0.6336458977384846, 0.6103966849577666]	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