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---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-13b-hf
model-index:
- name: lora-out
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
# lora-out
This model is a fine-tuned version of [codellama/CodeLlama-13b-hf](https://huggingface.co./codellama/CodeLlama-13b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4263
## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7628 | 0.01 | 1 | 0.7296 |
| 0.7101 | 0.05 | 7 | 0.6906 |
| 0.5395 | 0.1 | 14 | 0.5214 |
| 0.5303 | 0.15 | 21 | 0.4871 |
| 0.4821 | 0.2 | 28 | 0.4676 |
| 0.5643 | 0.25 | 35 | 0.4563 |
| 0.5307 | 0.3 | 42 | 0.4484 |
| 0.5103 | 0.35 | 49 | 0.4445 |
| 0.5515 | 0.4 | 56 | 0.4415 |
| 0.4983 | 0.45 | 63 | 0.4386 |
| 0.4919 | 0.5 | 70 | 0.4351 |
| 0.4674 | 0.55 | 77 | 0.4316 |
| 0.5193 | 0.6 | 84 | 0.4295 |
| 0.4461 | 0.65 | 91 | 0.4295 |
| 0.4541 | 0.71 | 98 | 0.4280 |
| 0.486 | 0.76 | 105 | 0.4280 |
| 0.4875 | 0.81 | 112 | 0.4269 |
| 0.5553 | 0.86 | 119 | 0.4266 |
| 0.4605 | 0.91 | 126 | 0.4260 |
| 0.4767 | 0.96 | 133 | 0.4263 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
## Training procedure
### Framework versions
- PEFT 0.6.0
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