---
base_model: "mistralai/Mistral-Nemo-Instruct-2407"
library_name: peft
tags:
- lora
- adapter
---

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# lora

This model is a fine-tuned version of [mistralai/Mistral-Nemo-Instruct-2407](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407) on the ft_01KSWQ2Z_d0, the ft_01KSWQ2Z_d1, the ft_01KSWQ2Z_d2, the ft_01KSWQ2Z_d3, the ft_01KSWQ2Z_d4 and the ft_01KSWQ2Z_d5 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.7760

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8569        | 0.2903 | 100  | 0.8779          |
| 0.8435        | 0.5806 | 200  | 0.8248          |
| 0.7267        | 0.8708 | 300  | 0.8032          |
| 0.7409        | 1.1597 | 400  | 0.7901          |
| 0.663         | 1.4499 | 500  | 0.7802          |
| 0.7083        | 1.7402 | 600  | 0.7767          |


### Framework versions

- PEFT 0.19.1
- Transformers 4.57.1
- Pytorch 2.10.0+rocm7.0
- Datasets 4.0.0
- Tokenizers 0.22.2