---
library_name: peft
license: apache-2.0
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
tags:
- base_model:adapter:TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: tabeehive-ft-2
  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. -->

# tabeehive-ft-2

This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6212

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT 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: 2
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.7337        | 1.0   | 3    | 2.4865          |
| 2.3332        | 2.0   | 6    | 2.0148          |
| 1.9239        | 3.0   | 9    | 1.7024          |
| 1.6376        | 4.0   | 12   | 1.4442          |
| 1.3897        | 5.0   | 15   | 1.2083          |
| 1.1686        | 6.0   | 18   | 1.0030          |
| 0.9796        | 7.0   | 21   | 0.8399          |
| 0.8304        | 8.0   | 24   | 0.7174          |
| 0.7297        | 9.0   | 27   | 0.6498          |
| 0.6753        | 10.0  | 30   | 0.6212          |


### Framework versions

- PEFT 0.16.0
- Transformers 4.53.1
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.2