---
library_name: peft
license: apache-2.0
base_model: unsloth/Mistral-Nemo-Instruct-2407
tags:
- axolotl
- generated_from_trainer
model-index:
- name: a91fc4a2-b06c-401e-aa8c-fa38c7498198
  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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<br>

# a91fc4a2-b06c-401e-aa8c-fa38c7498198

This model is a fine-tuned version of [unsloth/Mistral-Nemo-Instruct-2407](https://huggingface.co/unsloth/Mistral-Nemo-Instruct-2407) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3227

## 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: 0.000201
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0009 | 1    | 0.6020          |
| 0.0242        | 0.0438 | 50   | 0.4622          |
| 0.0135        | 0.0875 | 100  | 0.4963          |
| 0.003         | 0.1313 | 150  | 0.5679          |
| 0.0059        | 0.1751 | 200  | 0.4313          |
| 0.0031        | 0.2188 | 250  | 0.4164          |
| 0.0057        | 0.2626 | 300  | 0.4199          |
| 0.0057        | 0.3063 | 350  | 0.3514          |
| 0.001         | 0.3501 | 400  | 0.3395          |
| 0.0019        | 0.3939 | 450  | 0.3236          |
| 0.002         | 0.4376 | 500  | 0.3227          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1