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

Loss: 1.4164
Accuracy: 0.8011

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.9713	1.0	2774	3.0764	0.1615
1.7443	2.0	5549	1.8279	0.4734
1.1304	3.0	8323	1.3202	0.6371
1.2718	4.0	11098	1.1571	0.6968
0.769	5.0	13872	1.2917	0.7127
0.2656	6.0	16647	1.1549	0.7479
0.2939	7.0	19421	1.2372	0.7736
0.1278	8.0	22196	1.2985	0.7875
0.5175	9.0	24970	1.3664	0.7986
0.0547	10.0	27740	1.4164	0.8011

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

AescF/hubert-base-ls960-finetuned-common_language

hubert-base-ls960-finetuned-common_language-finetuned-common_language

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

AescF/
hubert-base-ls960-finetuned-common_language