biomistral-gptq-ft / README.md
amasi's picture
amasi/biomistral-gptq-ft
8f2328a verified
---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: LoneStriker/BioMistral-7B-SLERP-GPTQ
model-index:
- name: biomistral-gptq-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. -->
# biomistral-gptq-ft
This model is a fine-tuned version of [LoneStriker/BioMistral-7B-SLERP-GPTQ](https://huggingface.co/LoneStriker/BioMistral-7B-SLERP-GPTQ) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3391
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9096 | 1.0 | 62 | 1.3700 |
| 1.3713 | 1.99 | 124 | 1.3455 |
| 1.3253 | 2.99 | 186 | 1.3391 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2