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metadata
library_name: peft
tags:
  - trl
  - sft
  - generated_from_trainer
datasets:
  - dialogstudio
base_model: NousResearch/Llama-2-7b-hf
model-index:
  - name: llama2-7b-tweet-summarization
    results: []

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