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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: llama2-7bb-tweet-summarization-gradnorm-0.3
    results: []

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