---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
model-index:
- name: shakespeare-ft
  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. -->
# Cite 
This model is trained from the code in this [GitHub](https://github.com/ShawhinT/YouTube-Blog/tree/main/LLMs/qlora)
# shakespeare-ft

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 an [Lambent/shakespeare_sonnets_backtranslated](https://huggingface.co/datasets/Lambent/shakespeare_sonnets_backtranslated) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7122

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 16
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3058        | 0.97  | 15   | 1.2255          |
| 1.017         | 2.0   | 31   | 1.1220          |
| 0.9377        | 2.97  | 46   | 1.0527          |
| 0.7699        | 4.0   | 62   | 0.9921          |
| 0.728         | 4.97  | 77   | 0.9438          |
| 0.6098        | 6.0   | 93   | 0.8995          |
| 0.5781        | 6.97  | 108  | 0.8649          |
| 0.4823        | 8.0   | 124  | 0.8288          |
| 0.4598        | 8.97  | 139  | 0.8065          |
| 0.3866        | 10.0  | 155  | 0.7736          |
| 0.3693        | 10.97 | 170  | 0.7525          |
| 0.3165        | 12.0  | 186  | 0.7422          |
| 0.312         | 12.97 | 201  | 0.7276          |
| 0.2761        | 14.0  | 217  | 0.7160          |
| 0.2815        | 14.97 | 232  | 0.7121          |
| 0.2463        | 15.48 | 240  | 0.7122          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2