finetuned-beit-limb-seq-t2-8heads-1layers-2.5e-4lr

This model is a fine-tuned version of c14kevincardenas/beit-large-patch16-384-limb-person-crop on the c14kevincardenas/beta_caller_284_person_crop_seq_withlimb_2 dataset. It achieves the following results on the evaluation set:

• Loss: 0.5353
• Accuracy: 0.8847

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: 0.00025
• train_batch_size: 16
• eval_batch_size: 16
• seed: 2014
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 250
• num_epochs: 25.0
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.05

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8925	1.0	362	0.7904	0.7449
0.858	2.0	724	0.8538	0.7175
0.8091	3.0	1086	0.9683	0.7019
0.7739	4.0	1448	0.7409	0.7957
0.7614	5.0	1810	0.7168	0.8035
0.8067	6.0	2172	0.7570	0.8006
0.749	7.0	2534	0.8142	0.7634
0.7555	8.0	2896	0.6704	0.8319
0.6637	9.0	3258	0.6815	0.8231
0.6502	10.0	3620	0.6419	0.8543
0.6432	11.0	3982	0.6516	0.8504
0.6431	12.0	4344	0.6119	0.8631
0.6504	13.0	4706	0.5947	0.8631
0.5558	14.0	5068	0.5988	0.8602
0.53	15.0	5430	0.5833	0.8700
0.6418	16.0	5792	0.6134	0.8710
0.5703	17.0	6154	0.6183	0.8700
0.5244	18.0	6516	0.5692	0.8680
0.5311	19.0	6878	0.5639	0.8661
0.5504	20.0	7240	0.5518	0.8837
0.4922	21.0	7602	0.5777	0.8671
0.4801	22.0	7964	0.5549	0.8778
0.5085	23.0	8326	0.5502	0.8768
0.5002	24.0	8688	0.5445	0.8856
0.4404	25.0	9050	0.5353	0.8847

Framework versions

• Transformers 4.43.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.19.1
• Tokenizers 0.19.1