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---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-7b-hf
model-index:
- name: sql-code-llama
results: []
---
<!-- 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: 0.4583
## 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: 0.0003
- 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2023 | 0.04 | 20 | 2.0520 |
| 1.212 | 0.07 | 40 | 0.8926 |
| 0.8532 | 0.11 | 60 | 0.7526 |
| 0.5953 | 0.14 | 80 | 0.5960 |
| 0.3869 | 0.18 | 100 | 0.5596 |
| 0.5738 | 0.22 | 120 | 0.5181 |
| 0.4281 | 0.25 | 140 | 0.5080 |
| 0.6451 | 0.29 | 160 | 0.5146 |
| 0.4874 | 0.33 | 180 | 0.4893 |
| 0.3588 | 0.36 | 200 | 0.5016 |
| 0.5308 | 0.4 | 220 | 0.4816 |
| 0.4006 | 0.43 | 240 | 0.4777 |
| 0.5958 | 0.47 | 260 | 0.4780 |
| 0.4682 | 0.51 | 280 | 0.4685 |
| 0.3507 | 0.54 | 300 | 0.4753 |
| 0.5079 | 0.58 | 320 | 0.4664 |
| 0.3933 | 0.62 | 340 | 0.4626 |
| 0.5839 | 0.65 | 360 | 0.4622 |
| 0.4543 | 0.69 | 380 | 0.4594 |
| 0.3475 | 0.72 | 400 | 0.4583 |
### Framework versions
- PEFT 0.10.1.dev0
- Transformers 4.36.0
- Pytorch 2.0.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2 |