Instructions to use wesleyaag/data2vec-squad-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wesleyaag/data2vec-squad-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="wesleyaag/data2vec-squad-test")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("wesleyaag/data2vec-squad-test") model = AutoModelForQuestionAnswering.from_pretrained("wesleyaag/data2vec-squad-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - en | |
| datasets: | |
| - squad | |
| model: | |
| - facebook/data2vec-text-base | |
| <h1>data2vec squad</h1> | |
| This is a testing fine tuned data2vec model in the squad dataset, any improvements and suggestions are welcome! | |
| <h3>Intended use</h3> | |
| Question Answering | |
| <h3>Training results</h3> | |
| <table> | |
| <thead> | |
| <tr> | |
| <th>Epoch</th> | |
| <th>Training Loss</th> | |
| <th>Validation Loss</th> | |
| </tr> | |
| </thead> | |
| <tbody> | |
| <tr> | |
| <td>1</td> | |
| <td><span style="font-family: Roboto, Noto, sans-serif; font-size: 14px; font-style: normal; font-weight: 400; text-align: right;">1.015800</span><br></td> | |
| <td><span style="font-family: Roboto, Noto, sans-serif; font-size: 14px; font-style: normal; font-weight: 400; text-align: right;">0.997690</span><br></td> | |
| </tr> | |
| <tr> | |
| <td>2</td> | |
| <td><span style="font-family: Roboto, Noto, sans-serif; font-size: 14px; font-style: normal; font-weight: 400; text-align: right;">0.804400</span></td> | |
| <td><span style="font-family: Roboto, Noto, sans-serif; font-size: 14px; font-style: normal; font-weight: 400; text-align: right;">0.950322</span><br></td> | |
| </tr> | |
| </tbody> | |
| </table> | |
| <h3>Hyperparameters</h3> | |
| <ul> | |
| <li>evaluation_strategy="epoch"</li> | |
| <li>learning_rate=2e-5</li> | |
| <li>per_device_train_batch_size=15</li> | |
| <li>per_device_eval_batch_size=15</li> | |
| <li>num_train_epochs=2</li> | |
| <li>weight_decay=0.01</li> | |
| </ul> | |
| <h3>Frameworks and libraries used:</h3> | |
| <ul> | |
| <li>transformers</li> | |
| <li>datasets</li> | |
| <li>evaluate</li> | |
| </ul> |