Hugging Face's logo

CHAFIK12
/
second_sql_converter_model

PEFT
Safetensors
Generated from Trainer
Model card Files Community
second_sql_converter_model / README.md
CHAFIK12's picture
CHAFIK12
End of training
5ac296b verified
preview code
|
raw
history blame contribute delete
3.15 kB
metadata
license: llama2
base_model: codellama/CodeLlama-7b-hf
tags:
  - generated_from_trainer
model-index:
  - name: fine_tuning_codellama
    results: []
library_name: peft

Visualize in Weights & Biases

fine_tuning_codellama

This model is a fine-tuned version of codellama/CodeLlama-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1513

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: True
  • _load_in_4bit: False
  • 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: fp4
  • bnb_4bit_use_double_quant: False
  • bnb_4bit_compute_dtype: float32
  • bnb_4bit_quant_storage: uint8
  • load_in_4bit: False
  • load_in_8bit: True

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • training_steps: 400
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
1.1085 0.1010 20 1.0942
0.729 0.2020 40 0.5856
0.4941 0.3030 60 0.3775
0.2508 0.4040 80 0.2868
0.2139 0.5051 100 0.2528
0.2612 0.6061 120 0.2115
0.154 0.7071 140 0.2073
0.2558 0.8081 160 0.1936
0.1553 0.9091 180 0.1832
0.1831 1.0101 200 0.1872
0.2135 1.1111 220 0.1729
0.1278 1.2121 240 0.1724
0.21 1.3131 260 0.1676
0.1328 1.4141 280 0.1619
0.1731 1.5152 300 0.1651
0.1668 1.6162 320 0.1577
0.1259 1.7172 340 0.1565
0.191 1.8182 360 0.1543
0.129 1.9192 380 0.1515
0.1693 2.0202 400 0.1513

Framework versions

  • PEFT 0.6.0.dev0
  • Transformers 4.42.0.dev0
  • Pytorch 2.1.2
  • Datasets 2.19.2
  • Tokenizers 0.19.1