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---
license: llama2
base_model: codellama/CodeLlama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: sql-code-llama
results: []
library_name: peft
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# sql-code-llama
This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4577
## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.1953 | 0.0465 | 20 | 2.0335 |
| 1.1292 | 0.0931 | 40 | 0.8342 |
| 0.8133 | 0.1396 | 60 | 0.6552 |
| 0.5873 | 0.1862 | 80 | 0.5861 |
| 0.4095 | 0.2327 | 100 | 0.5589 |
| 0.5731 | 0.2792 | 120 | 0.5159 |
| 0.4221 | 0.3258 | 140 | 0.5039 |
| 0.6365 | 0.3723 | 160 | 0.5159 |
| 0.4779 | 0.4188 | 180 | 0.4867 |
| 0.3584 | 0.4654 | 200 | 0.5007 |
| 0.5325 | 0.5119 | 220 | 0.4802 |
| 0.3998 | 0.5585 | 240 | 0.4767 |
| 0.5952 | 0.6050 | 260 | 0.4777 |
| 0.4649 | 0.6515 | 280 | 0.4671 |
| 0.3394 | 0.6981 | 300 | 0.4752 |
| 0.5084 | 0.7446 | 320 | 0.4669 |
| 0.3934 | 0.7912 | 340 | 0.4613 |
| 0.5762 | 0.8377 | 360 | 0.4617 |
| 0.4563 | 0.8842 | 380 | 0.4586 |
| 0.345 | 0.9308 | 400 | 0.4577 |
### Framework versions
- PEFT 0.6.0.dev0
- Transformers 4.44.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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