---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: norallm/normistral-7b-warm
datasets:
- hugodk-sch/aftonposten_title_sft
model-index:
- name: ap-normistral-7b-sft-qlora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ap-normistral-7b-sft-qlora

This model is a fine-tuned version of [norallm/normistral-7b-warm](https://huggingface.co/norallm/normistral-7b-warm) on the hugodk-sch/aftonposten_title_sft dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6055

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 2.063         | 1.0   | 264  | 2.1618          |
| 1.2293        | 2.0   | 528  | 1.9121          |
| 0.6985        | 3.0   | 792  | 1.6916          |
| 0.4922        | 4.0   | 1056 | 1.6054          |
| 0.3396        | 5.0   | 1320 | 1.6055          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.1