metadata

library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: hubert-base-ls960-2clsfinetuned-bmd-V1-20250201_145011-LOSO-section-out5
    results: []

hubert-base-ls960-2clsfinetuned-bmd-V1-20250201_145011-LOSO-section-out5

This model is a fine-tuned version of facebook/hubert-base-ls960 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7381
Accuracy: 0.7273
F1: 0.7273
Precision: 0.7273
Recall: 0.7273

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: 4
eval_batch_size: 4
seed: 1968
gradient_accumulation_steps: 4
total_train_batch_size: 16
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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	5	0.6674	0.5909	0.5087	0.775	0.5909
0.6794	2.0	10	0.6130	0.7727	0.7723	0.775	0.7727
0.6794	3.0	15	0.6236	0.6818	0.6645	0.7292	0.6818
0.5818	4.0	20	0.6672	0.6364	0.5810	0.7895	0.6364
0.5818	5.0	25	0.5214	0.7727	0.7723	0.775	0.7727
0.49	6.0	30	0.5402	0.7273	0.7273	0.7273	0.7273
0.49	7.0	35	0.7001	0.5455	0.5089	0.5647	0.5455
0.3862	8.0	40	0.5804	0.8182	0.8167	0.8291	0.8182
0.3862	9.0	45	0.6310	0.8182	0.8167	0.8291	0.8182
0.2812	10.0	50	0.7381	0.7273	0.7273	0.7273	0.7273

Framework versions

Transformers 4.48.2
Pytorch 2.5.1+cu124
Datasets 3.2.0
Tokenizers 0.21.0