hubert-base-ls960-finetuned-common_language-finetuned-common_language
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
- Downloads last month
- 13
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for AescF/hubert-base-ls960-finetuned-common_language
Base model
facebook/hubert-base-ls960Dataset used to train AescF/hubert-base-ls960-finetuned-common_language
Space using AescF/hubert-base-ls960-finetuned-common_language 1
Evaluation results
- Accuracy on Common Languagetest set self-reported0.801