|
--- |
|
license: llama2 |
|
library_name: peft |
|
tags: |
|
- generated_from_trainer |
|
base_model: codellama/CodeLlama-13b-Instruct-hf |
|
model-index: |
|
- name: lora-out |
|
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. --> |
|
|
|
[<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-Instruct-hf](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4172 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 0.7046 | 0.01 | 1 | 0.6695 | |
|
| 0.6348 | 0.05 | 7 | 0.6183 | |
|
| 0.5056 | 0.1 | 14 | 0.4993 | |
|
| 0.5127 | 0.15 | 21 | 0.4682 | |
|
| 0.4663 | 0.2 | 28 | 0.4552 | |
|
| 0.5534 | 0.25 | 35 | 0.4419 | |
|
| 0.5231 | 0.3 | 42 | 0.4369 | |
|
| 0.5045 | 0.35 | 49 | 0.4338 | |
|
| 0.5444 | 0.4 | 56 | 0.4314 | |
|
| 0.4922 | 0.45 | 63 | 0.4296 | |
|
| 0.487 | 0.5 | 70 | 0.4261 | |
|
| 0.4627 | 0.55 | 77 | 0.4230 | |
|
| 0.5143 | 0.6 | 84 | 0.4210 | |
|
| 0.4429 | 0.65 | 91 | 0.4199 | |
|
| 0.4491 | 0.71 | 98 | 0.4193 | |
|
| 0.4808 | 0.76 | 105 | 0.4188 | |
|
| 0.483 | 0.81 | 112 | 0.4176 | |
|
| 0.5513 | 0.86 | 119 | 0.4177 | |
|
| 0.4574 | 0.91 | 126 | 0.4170 | |
|
| 0.4723 | 0.96 | 133 | 0.4172 | |
|
|
|
|
|
### 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 |
|
|
