File size: 1,969 Bytes
85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b 85dbe7c 04a856b |
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 |
---
base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
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: 1.7362
## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 4.5901 | 0.9231 | 3 | 3.9541 |
| 4.0291 | 1.8462 | 6 | 3.4199 |
| 3.445 | 2.7692 | 9 | 2.9590 |
| 2.2321 | 4.0 | 13 | 2.5259 |
| 2.6077 | 4.9231 | 16 | 2.2507 |
| 2.2579 | 5.8462 | 19 | 2.0273 |
| 1.9983 | 6.7692 | 22 | 1.8818 |
| 1.4141 | 8.0 | 26 | 1.7787 |
| 1.8067 | 8.9231 | 29 | 1.7407 |
| 1.2606 | 9.2308 | 30 | 1.7362 |
### Framework versions
- PEFT 0.13.2
- Transformers 4.44.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.19.1 |