Instructions to use fadhilarkan/qa-indo-k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fadhilarkan/qa-indo-k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="fadhilarkan/qa-indo-k")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("fadhilarkan/qa-indo-k") model = AutoModelForQuestionAnswering.from_pretrained("fadhilarkan/qa-indo-k") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Error:"model-index[0].results" is required
qa-indo-k
This model was trained from scratch on an unkown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4984
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.2537 | 1.0 | 8209 | 1.9642 |
| 0.943 | 2.0 | 16418 | 2.2143 |
| 0.6694 | 3.0 | 24627 | 2.4984 |
Framework versions
- Transformers 4.6.1
- Pytorch 1.7.0
- Datasets 1.11.0
- Tokenizers 0.10.3
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