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---
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 Talebi S. YouTube-Blog. 2024. https://github.com/ShawhinT/YouTube-Blog
# 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 |