File size: 1,970 Bytes
ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 ec1e36f 8c01d18 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
model-index:
- name: shawgpt-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. -->
# shawgpt-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 unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8938
## 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.594 | 0.9231 | 3 | 3.9676 |
| 4.0507 | 1.8462 | 6 | 3.4506 |
| 3.4799 | 2.7692 | 9 | 3.0008 |
| 2.269 | 4.0 | 13 | 2.5789 |
| 2.703 | 4.9231 | 16 | 2.3498 |
| 2.3989 | 5.8462 | 19 | 2.1616 |
| 2.1824 | 6.7692 | 22 | 2.0223 |
| 1.5647 | 8.0 | 26 | 1.9752 |
| 2.0285 | 8.9231 | 29 | 1.9046 |
| 1.39 | 9.2308 | 30 | 1.8938 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1 |