---
license: apache-2.0
library_name: peft
tags:
- unsloth
- generated_from_trainer
base_model: unsloth/llama-2-13b-bnb-4bit
model-index:
- name: llama_2_13b_Magiccoder_evol_10k_qlora_ortho
  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. -->

# llama_2_13b_Magiccoder_evol_10k_qlora_ortho

This model is a fine-tuned version of [unsloth/llama-2-13b-bnb-4bit](https://huggingface.co/unsloth/llama-2-13b-bnb-4bit) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0950

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.2067        | 0.0262 | 4    | 1.1823          |
| 1.1675        | 0.0523 | 8    | 1.1498          |
| 1.1004        | 0.0785 | 12   | 1.1349          |
| 1.0531        | 0.1047 | 16   | 1.1288          |
| 1.0946        | 0.1308 | 20   | 1.1246          |
| 1.0602        | 0.1570 | 24   | 1.1215          |
| 1.0636        | 0.1832 | 28   | 1.1175          |
| 1.1078        | 0.2093 | 32   | 1.1151          |
| 1.04          | 0.2355 | 36   | 1.1125          |
| 1.115         | 0.2617 | 40   | 1.1123          |
| 1.0994        | 0.2878 | 44   | 1.1102          |
| 1.1379        | 0.3140 | 48   | 1.1098          |
| 1.1145        | 0.3401 | 52   | 1.1064          |
| 1.0849        | 0.3663 | 56   | 1.1088          |
| 1.1317        | 0.3925 | 60   | 1.1087          |
| 1.134         | 0.4186 | 64   | 1.1056          |
| 1.0856        | 0.4448 | 68   | 1.1038          |
| 1.0972        | 0.4710 | 72   | 1.1004          |
| 1.044         | 0.4971 | 76   | 1.1005          |
| 1.1311        | 0.5233 | 80   | 1.1004          |
| 1.1474        | 0.5495 | 84   | 1.1002          |
| 1.0886        | 0.5756 | 88   | 1.0999          |
| 1.0372        | 0.6018 | 92   | 1.0973          |
| 1.0376        | 0.6280 | 96   | 1.0968          |
| 1.1006        | 0.6541 | 100  | 1.0965          |
| 1.09          | 0.6803 | 104  | 1.0964          |
| 1.0786        | 0.7065 | 108  | 1.0969          |
| 1.111         | 0.7326 | 112  | 1.0970          |
| 1.053         | 0.7588 | 116  | 1.0961          |
| 1.0764        | 0.7850 | 120  | 1.0948          |
| 1.0971        | 0.8111 | 124  | 1.0944          |
| 1.0572        | 0.8373 | 128  | 1.0948          |
| 0.999         | 0.8635 | 132  | 1.0949          |
| 1.1098        | 0.8896 | 136  | 1.0951          |
| 1.0215        | 0.9158 | 140  | 1.0951          |
| 1.0759        | 0.9419 | 144  | 1.0951          |
| 1.096         | 0.9681 | 148  | 1.0950          |
| 1.08          | 0.9943 | 152  | 1.0950          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1