---
library_name: peft
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- base_model:adapter:mistralai/Mistral-7B-v0.1
- transformers
pipeline_tag: text-generation
model-index:
- name: Mistral-7B-v0.1-IA3-MathReasoning1
  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. -->

# Mistral-7B-v0.1-IA3-MathReasoning1

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4240

## 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: 2
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.4834        | 0.2667 | 100  | 0.6361          |
| 0.5032        | 0.5333 | 200  | 0.5080          |
| 0.4852        | 0.8    | 300  | 0.4864          |
| 0.468         | 1.0667 | 400  | 0.4705          |
| 0.4525        | 1.3333 | 500  | 0.4573          |
| 0.4355        | 1.6    | 600  | 0.4467          |
| 0.4218        | 1.8667 | 700  | 0.4381          |
| 0.4277        | 2.1333 | 800  | 0.4315          |
| 0.4126        | 2.4    | 900  | 0.4269          |
| 0.4132        | 2.6667 | 1000 | 0.4240          |
| 0.4222        | 2.9333 | 1100 | 0.4228          |


### Framework versions

- PEFT 0.17.1
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1