Instructions to use shayonhuggingface/phobert-v2-mtl-sequence-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shayonhuggingface/phobert-v2-mtl-sequence-classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shayonhuggingface/phobert-v2-mtl-sequence-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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phobert-v2-mtl-sequence-classification
This model is a fine-tuned version of on an unknown dataset.
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3
- Downloads last month
- 4
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