Instructions to use srinidhiskanda/QA_model_with_squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srinidhiskanda/QA_model_with_squad with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="srinidhiskanda/QA_model_with_squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("srinidhiskanda/QA_model_with_squad") model = AutoModelForQuestionAnswering.from_pretrained("srinidhiskanda/QA_model_with_squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
srinidhiskanda/QA_model_with_squad
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.3466
- Validation Loss: 1.5634
- Epoch: 2
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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 2.9258 | 1.8042 | 0 |
| 1.5529 | 1.5634 | 1 |
| 1.3466 | 1.5634 | 2 |
Framework versions
- Transformers 4.57.3
- TensorFlow 2.19.0
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for srinidhiskanda/QA_model_with_squad
Base model
distilbert/distilbert-base-uncased