---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- unsloth
- unsloth
- unsloth
- generated_from_trainer
base_model: unsloth/mistral-7b-instruct-v0.2-bnb-4bit
model-index:
- name: mistral-7b-instruct-v0.2-bnb-4bit1024
  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-instruct-v0.2-bnb-4bit1024

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6953

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8431        | 0.02  | 25   | 1.4131          |
| 0.8021        | 0.04  | 50   | 0.7911          |
| 0.7972        | 0.05  | 75   | 0.7886          |
| 0.7886        | 0.07  | 100  | 0.7780          |
| 0.7762        | 0.09  | 125  | 0.7546          |
| 0.7338        | 0.11  | 150  | 0.7332          |
| 0.707         | 0.12  | 175  | 0.7399          |
| 0.7252        | 0.14  | 200  | 0.7303          |
| 0.7513        | 0.16  | 225  | 0.7384          |
| 0.7275        | 0.18  | 250  | 0.7380          |
| 0.7283        | 0.19  | 275  | 0.7285          |
| 0.7132        | 0.21  | 300  | 0.7452          |
| 0.7273        | 0.23  | 325  | 0.7370          |
| 0.7353        | 0.25  | 350  | 0.7388          |
| 0.7457        | 0.27  | 375  | 0.7292          |
| 0.7404        | 0.28  | 400  | 0.7315          |
| 0.7312        | 0.3   | 425  | 0.7341          |
| 0.7285        | 0.32  | 450  | 0.7277          |
| 0.7331        | 0.34  | 475  | 0.7318          |
| 0.7179        | 0.35  | 500  | 0.7401          |
| 0.7432        | 0.37  | 525  | 0.7399          |
| 0.7305        | 0.39  | 550  | 0.7463          |
| 0.723         | 0.41  | 575  | 0.7448          |
| 0.7303        | 0.42  | 600  | 0.7339          |
| 0.7213        | 0.44  | 625  | 0.7320          |
| 0.7236        | 0.46  | 650  | 0.7378          |
| 0.7263        | 0.48  | 675  | 0.7451          |
| 0.7462        | 0.5   | 700  | 0.7238          |
| 0.7287        | 0.51  | 725  | 0.7274          |
| 0.7364        | 0.53  | 750  | 0.7369          |
| 0.7276        | 0.55  | 775  | 0.7282          |
| 0.7268        | 0.57  | 800  | 0.7431          |
| 0.7382        | 0.58  | 825  | 0.7376          |
| 0.7185        | 0.6   | 850  | 0.7402          |
| 0.7153        | 0.62  | 875  | 0.7362          |
| 0.7314        | 0.64  | 900  | 0.7395          |
| 0.7465        | 0.65  | 925  | 0.7378          |
| 0.7228        | 0.67  | 950  | 0.7333          |
| 0.7336        | 0.69  | 975  | 0.7337          |
| 0.72          | 0.71  | 1000 | 0.7313          |
| 0.7258        | 0.73  | 1025 | 0.7379          |
| 0.7312        | 0.74  | 1050 | 0.7342          |
| 0.7268        | 0.76  | 1075 | 0.7350          |
| 0.7137        | 0.78  | 1100 | 0.7401          |
| 0.7277        | 0.8   | 1125 | 0.7277          |
| 0.7314        | 0.81  | 1150 | 0.7388          |
| 0.7106        | 0.83  | 1175 | 0.7371          |
| 0.7226        | 0.85  | 1200 | 0.7326          |
| 0.7262        | 0.87  | 1225 | 0.7328          |
| 0.7356        | 0.88  | 1250 | 0.7408          |
| 0.7245        | 0.9   | 1275 | 0.7365          |
| 0.7221        | 0.92  | 1300 | 0.7404          |
| 0.7194        | 0.94  | 1325 | 0.7418          |
| 0.7209        | 0.96  | 1350 | 0.7380          |
| 0.7205        | 0.97  | 1375 | 0.7279          |
| 0.6788        | 0.99  | 1400 | 0.6953          |


### Framework versions

- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.1