This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the Dataset-t-t-t-t-t-t-t-t/UltraMed dataset. It achieves the following results on the evaluation set:

Loss: 0.1659

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
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.4852	1.0	134	0.1659

Framework versions

PEFT 0.13.0
Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0

Dataset-t-t-t-t-t-t-t-t/zephyr-7b-sft-qlora

zephyr-7b-sft-qlora

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Dataset-t-t-t-t-t-t-t-t/
zephyr-7b-sft-qlora