---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- unsloth
- generated_from_trainer
base_model: unsloth/mistral-7b-instruct-v0.2-bnb-4bit
model-index:
- name: mistral-inst_10000_200
  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-inst_10000_200

This model is a fine-tuned version of [unsloth/mistral-7b-instruct-v0.2-bnb-4bit](https://huggingface.co/unsloth/mistral-7b-instruct-v0.2-bnb-4bit) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3962

## 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: 8
- eval_batch_size: 4
- seed: 3407
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4844        | 0.31  | 48   | 1.1183          |
| 1.1246        | 0.61  | 96   | 1.0908          |
| 1.1002        | 0.92  | 144  | 1.0744          |
| 0.9854        | 1.23  | 192  | 1.0764          |
| 0.9533        | 1.54  | 240  | 1.0738          |
| 0.9392        | 1.84  | 288  | 1.0642          |
| 0.8426        | 2.15  | 336  | 1.1302          |
| 0.741         | 2.46  | 384  | 1.1290          |
| 0.7343        | 2.76  | 432  | 1.1219          |
| 0.7004        | 3.07  | 480  | 1.2799          |
| 0.5405        | 3.38  | 528  | 1.2481          |
| 0.538         | 3.69  | 576  | 1.2538          |
| 0.5379        | 3.99  | 624  | 1.2606          |
| 0.4171        | 4.3   | 672  | 1.3919          |
| 0.4156        | 4.61  | 720  | 1.3977          |
| 0.4168        | 4.92  | 768  | 1.3962          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.2