---
base_model: TinyLlama/TinyLlama_v1.1
library_name: peft
license: apache-2.0
tags:
- unsloth
- generated_from_trainer
model-index:
- name: tinyllama_magiccoder_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. -->

# tinyllama_magiccoder_ortho

This model is a fine-tuned version of [TinyLlama/TinyLlama_v1.1](https://huggingface.co./TinyLlama/TinyLlama_v1.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4401

## 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_ratio: 0.02
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8608        | 0.0262 | 4    | 1.8810          |
| 1.7875        | 0.0523 | 8    | 1.6839          |
| 1.6211        | 0.0785 | 12   | 1.6379          |
| 1.5275        | 0.1047 | 16   | 1.5652          |
| 1.5674        | 0.1308 | 20   | 1.5608          |
| 1.4798        | 0.1570 | 24   | 1.5422          |
| 1.484         | 0.1832 | 28   | 1.5231          |
| 1.524         | 0.2093 | 32   | 1.5137          |
| 1.4406        | 0.2355 | 36   | 1.5169          |
| 1.5328        | 0.2617 | 40   | 1.5073          |
| 1.5037        | 0.2878 | 44   | 1.4938          |
| 1.5445        | 0.3140 | 48   | 1.4939          |
| 1.5157        | 0.3401 | 52   | 1.4924          |
| 1.4724        | 0.3663 | 56   | 1.4748          |
| 1.5457        | 0.3925 | 60   | 1.4869          |
| 1.5126        | 0.4186 | 64   | 1.4744          |
| 1.4564        | 0.4448 | 68   | 1.4726          |
| 1.4628        | 0.4710 | 72   | 1.4695          |
| 1.4244        | 0.4971 | 76   | 1.4711          |
| 1.5274        | 0.5233 | 80   | 1.4654          |
| 1.5459        | 0.5495 | 84   | 1.4615          |
| 1.4562        | 0.5756 | 88   | 1.4600          |
| 1.3771        | 0.6018 | 92   | 1.4578          |
| 1.3837        | 0.6280 | 96   | 1.4537          |
| 1.46          | 0.6541 | 100  | 1.4546          |
| 1.4711        | 0.6803 | 104  | 1.4554          |
| 1.4257        | 0.7065 | 108  | 1.4455          |
| 1.4661        | 0.7326 | 112  | 1.4473          |
| 1.4269        | 0.7588 | 116  | 1.4469          |
| 1.4269        | 0.7850 | 120  | 1.4433          |
| 1.4514        | 0.8111 | 124  | 1.4461          |
| 1.4349        | 0.8373 | 128  | 1.4458          |
| 1.3174        | 0.8635 | 132  | 1.4409          |
| 1.4861        | 0.8896 | 136  | 1.4399          |
| 1.3536        | 0.9158 | 140  | 1.4408          |
| 1.408         | 0.9419 | 144  | 1.4404          |
| 1.4435        | 0.9681 | 148  | 1.4401          |
| 1.4317        | 0.9943 | 152  | 1.4401          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1