epidemiology_sft_5000_mcq_1epoch

Howard881010/epidemiology_sft_5000_mcq_1epoch

epidemiology_sft_5000_mcq_1epoch is a machine learning model from Howard881010. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as other.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

24% of all-time downloads

All-time downloads

Public

Repo size

360 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.pt229 MB · 47%

At a glance

Library: peft
License: other
Access: Public
Created: Jan 16, 2025
Updated: Jan 16, 2025
SHA: 69646ca0

Base models

mistralai/Mistral-Nemo-Instruct-2407

Model card

From the Hugging Face model README

epidemiology_sft_5000_mcq_1epoch

This model is a fine-tuned version of mistralai/Mistral-Nemo-Instruct-2407 on the epidemiology_5000_mcq dataset. It achieves the following results on the evaluation set:

Loss: 0.0039

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: 0.0001
train_batch_size: 10
eval_batch_size: 10
seed: 42
distributed_type: multi-GPU
num_devices: 2
total_train_batch_size: 20
total_eval_batch_size: 20
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
0.0042	0.1333	30	0.0041
0.004	0.2667	60	0.0039
0.0039	0.4	90	0.0039
0.0039	0.5333	120	0.0040
0.0039	0.6667	150	0.0039
0.0039	0.8	180	0.0039
0.0039	0.9333	210	0.0039

Framework versions

PEFT 0.12.0
Transformers 4.46.0
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.20.1

Library: peft
License: other
Created: Jan 16, 2025
Updated: Jan 16, 2025