fine_tuning_llama_3 / README.md
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metadata
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
  - generated_from_trainer
datasets:
  - knkarthick/dialogsum
model-index:
  - name: fine_tuning_llama_4
    results: []

fine_tuning_llama_4

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

  • Loss: 1.1296

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
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss
0.9863 1.0 78 1.1460
1.0109 2.0 156 1.1343
0.9011 3.0 234 1.1301
0.9703 4.0 312 1.1296

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3