---
base_model: unsloth/Mistral-Nemo-Base-2407-bnb-4bit
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- unsloth
- generated_from_trainer
model-index:
- name: mistrial_nemo_output
  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. -->

# mistrial_nemo_output

This model is a fine-tuned version of [unsloth/Mistral-Nemo-Base-2407-bnb-4bit](https://huggingface.co/unsloth/Mistral-Nemo-Base-2407-bnb-4bit) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5118

## 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: 4
- eval_batch_size: 4
- seed: 100
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.7287        | 0.0516 | 20   | 1.7033          |
| 1.6508        | 0.1033 | 40   | 1.6490          |
| 1.6242        | 0.1549 | 60   | 1.6253          |
| 1.6216        | 0.2066 | 80   | 1.6089          |
| 1.619         | 0.2582 | 100  | 1.5958          |
| 1.5579        | 0.3099 | 120  | 1.5842          |
| 1.5578        | 0.3615 | 140  | 1.5739          |
| 1.5515        | 0.4132 | 160  | 1.5641          |
| 1.5739        | 0.4648 | 180  | 1.5550          |
| 1.5669        | 0.5165 | 200  | 1.5460          |
| 1.5601        | 0.5681 | 220  | 1.5380          |
| 1.5392        | 0.6198 | 240  | 1.5310          |
| 1.5321        | 0.6714 | 260  | 1.5251          |
| 1.5326        | 0.7230 | 280  | 1.5201          |
| 1.5197        | 0.7747 | 300  | 1.5165          |
| 1.5229        | 0.8263 | 320  | 1.5142          |
| 1.4988        | 0.8780 | 340  | 1.5127          |
| 1.5044        | 0.9296 | 360  | 1.5119          |
| 1.5105        | 0.9813 | 380  | 1.5118          |


### Framework versions

- PEFT 0.12.1.dev0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1