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---
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: NorLLM-AI/NorMistral-7B
datasets:
- generator
model-index:
- name: norllm-ai-normistral-7b-sft-qlora
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. -->
# norllm-ai-normistral-7b-sft-qlora
This model is a fine-tuned version of [NorLLM-AI/NorMistral-7B](https://huggingface.co/NorLLM-AI/NorMistral-7B) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4403
## 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: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.7274 | 1.0 | 274 | 1.9432 |
| 1.1514 | 2.0 | 549 | 1.7111 |
| 0.645 | 3.0 | 823 | 1.5109 |
| 0.4291 | 4.0 | 1098 | 1.4415 |
| 0.3392 | 4.99 | 1370 | 1.4403 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1 |