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metadata
license: llama2
base_model: meta-llama/Llama-2-7b-chat-hf
tags:
  - generated_from_trainer
model-index:
  - name: MSc_llama2_finetuned_model_secondData5
    results: []
library_name: peft

MSc_llama2_finetuned_model_secondData5

This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7187

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

The following bitsandbytes quantization config was used during training:

  • quant_method: bitsandbytes
  • _load_in_8bit: False
  • _load_in_4bit: True
  • llm_int8_threshold: 6.0
  • llm_int8_skip_modules: None
  • llm_int8_enable_fp32_cpu_offload: False
  • llm_int8_has_fp16_weight: False
  • bnb_4bit_quant_type: nf4
  • bnb_4bit_use_double_quant: True
  • bnb_4bit_compute_dtype: bfloat16
  • load_in_4bit: True
  • load_in_8bit: False

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 3e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • training_steps: 250

Training results

Training Loss Epoch Step Validation Loss
3.9919 1.36 10 3.6771
3.369 2.71 20 2.9923
2.6302 4.07 30 2.2344
1.9467 5.42 40 1.7496
1.5893 6.78 50 1.5028
1.2919 8.14 60 1.1706
0.9447 9.49 70 0.8988
0.8096 10.85 80 0.8443
0.745 12.2 90 0.8025
0.6904 13.56 100 0.7733
0.6546 14.92 110 0.7539
0.6267 16.27 120 0.7387
0.5954 17.63 130 0.7316
0.5799 18.98 140 0.7256
0.5596 20.34 150 0.7228
0.5432 21.69 160 0.7215
0.5389 23.05 170 0.7176
0.5234 24.41 180 0.7175
0.518 25.76 190 0.7189
0.5122 27.12 200 0.7177
0.5036 28.47 210 0.7185
0.5049 29.83 220 0.7191
0.5041 31.19 230 0.7195
0.5028 32.54 240 0.7188
0.4973 33.9 250 0.7187

Framework versions

  • PEFT 0.4.0
  • Transformers 4.38.2
  • Pytorch 2.3.1+cu121
  • Datasets 2.13.1
  • Tokenizers 0.15.2