rapper-gpt / README.md
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Maab9X9/rapper-gpt
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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: rapper-gpt
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. -->
# rapper-gpt
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 unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1394
## 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: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.0259 | 0.8889 | 4 | 0.9759 |
| 0.7299 | 2.0 | 9 | 0.9117 |
| 0.8055 | 2.8889 | 13 | 0.8819 |
| 0.5669 | 4.0 | 18 | 0.8468 |
| 0.622 | 4.8889 | 22 | 0.8584 |
| 0.4568 | 6.0 | 27 | 0.9003 |
| 0.5379 | 6.8889 | 31 | 0.9569 |
| 0.4119 | 8.0 | 36 | 0.9821 |
| 0.4993 | 8.8889 | 40 | 1.0176 |
| 0.3941 | 10.0 | 45 | 1.0345 |
| 0.4832 | 10.8889 | 49 | 1.0687 |
| 0.3836 | 12.0 | 54 | 1.0911 |
| 0.4758 | 12.8889 | 58 | 1.0688 |
| 0.3788 | 14.0 | 63 | 1.0902 |
| 0.4711 | 14.8889 | 67 | 1.0868 |
| 0.3749 | 16.0 | 72 | 1.0949 |
| 0.4663 | 16.8889 | 76 | 1.1072 |
| 0.3724 | 18.0 | 81 | 1.1164 |
| 0.464 | 18.8889 | 85 | 1.1282 |
| 0.3702 | 20.0 | 90 | 1.1350 |
| 0.4619 | 20.8889 | 94 | 1.1387 |
| 0.3684 | 22.0 | 99 | 1.1391 |
| 0.4108 | 22.2222 | 100 | 1.1394 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1