---
license: apache-2.0
base_model: mistralai/Mistral-7B-Instruct-v0.3
tags:
- generated_from_trainer
model-index:
- name: Mistral-7B-Instruct-v0.3-lora-commonsense
  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/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/yspkm/PrunePath-LoRA/runs/9c3s4ewl)
# Mistral-7B-Instruct-v0.3-lora-commonsense

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6863

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8738        | 0.1503 | 200  | 0.8158          |
| 0.8589        | 0.3006 | 400  | 0.7939          |
| 0.8589        | 0.4510 | 600  | 0.7800          |
| 0.8589        | 0.6013 | 800  | 0.7725          |
| 0.8305        | 0.7516 | 1000 | 0.7650          |
| 0.8331        | 0.9019 | 1200 | 0.7506          |
| 0.7808        | 1.0522 | 1400 | 0.7438          |
| 0.7781        | 1.2026 | 1600 | 0.7350          |
| 0.7647        | 1.3529 | 1800 | 0.7252          |
| 0.7651        | 1.5032 | 2000 | 0.7228          |
| 0.7522        | 1.6535 | 2200 | 0.7099          |
| 0.7587        | 1.8038 | 2400 | 0.6997          |
| 0.7383        | 1.9542 | 2600 | 0.6932          |
| 0.7071        | 2.1045 | 2800 | 0.6949          |
| 0.6919        | 2.2548 | 3000 | 0.6899          |
| 0.7136        | 2.4051 | 3200 | 0.6884          |
| 0.6912        | 2.5554 | 3400 | 0.6878          |
| 0.6889        | 2.7057 | 3600 | 0.6867          |
| 0.6862        | 2.8561 | 3800 | 0.6863          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1