metadata

library_name: transformers
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: hiera-finetuned-busi
    results: []

hiera-finetuned-busi

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1380
Accuracy: 0.9679
F1: 0.9678
Precision: 0.9678
Recall: 0.9679

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: 2e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
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_with_restarts
lr_scheduler_warmup_ratio: 0.1
num_epochs: 48
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.2276	10.0	100	0.1666	0.9615	0.9611	0.9640	0.9615
0.1447	20.0	200	0.1826	0.9359	0.9352	0.9426	0.9359
0.0882	30.0	300	0.1612	0.9615	0.9612	0.9613	0.9615
0.0606	40.0	400	0.1380	0.9679	0.9678	0.9678	0.9679

Framework versions

Transformers 4.53.1
Pytorch 2.7.1+cu126
Datasets 3.6.0
Tokenizers 0.21.2