Instructions to use hung200504/bert-21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hung200504/bert-21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hung200504/bert-21")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hung200504/bert-21") model = AutoModelForQuestionAnswering.from_pretrained("hung200504/bert-21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: cc-by-4.0 | |
| base_model: deepset/bert-base-cased-squad2 | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: bert-21 | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # bert-21 | |
| This model is a fine-tuned version of [deepset/bert-base-cased-squad2](https://huggingface.co/deepset/bert-base-cased-squad2) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 11.9330 | |
| ## 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: 3e-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: 1 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:-----:|:----:|:---------------:| | |
| | 11.3134 | 0.09 | 5 | 12.3068 | | |
| | 11.4146 | 0.18 | 10 | 12.2378 | | |
| | 10.9861 | 0.27 | 15 | 12.1756 | | |
| | 11.1036 | 0.36 | 20 | 12.1205 | | |
| | 11.079 | 0.45 | 25 | 12.0721 | | |
| | 11.1039 | 0.55 | 30 | 12.0310 | | |
| | 10.3894 | 0.64 | 35 | 11.9972 | | |
| | 11.034 | 0.73 | 40 | 11.9707 | | |
| | 10.6017 | 0.82 | 45 | 11.9511 | | |
| | 10.5161 | 0.91 | 50 | 11.9387 | | |
| | 10.3011 | 1.0 | 55 | 11.9330 | | |
| ### Framework versions | |
| - Transformers 4.34.1 | |
| - Pytorch 2.1.0+cu118 | |
| - Datasets 2.14.5 | |
| - Tokenizers 0.14.1 | |