This model is a fine-tuned version of 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

hugodk-sch/ap-normistral-7b-sft-qlora

ap-normistral-7b-sft-qlora

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hugodk-sch/
ap-normistral-7b-sft-qlora