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---
license: llama2
base_model: codellama/CodeLlama-7b-hf
tags:
- generated_from_trainer
model-index:
- name: fine_tuning_codellama
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/chebbichafik133/sql-convert/runs/3q5mg1tl)
# fine_tuning_codellama
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: 0.1513
## 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
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