Instructions to use horsbug98/Part_2_mBERT_Model_E2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use horsbug98/Part_2_mBERT_Model_E2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="horsbug98/Part_2_mBERT_Model_E2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("horsbug98/Part_2_mBERT_Model_E2") model = AutoModelForQuestionAnswering.from_pretrained("horsbug98/Part_2_mBERT_Model_E2") - Notebooks
- Google Colab
- Kaggle
Upload all_results.json
Browse files- all_results.json +11 -0
all_results.json
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{
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"epoch": 2.0,
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"eval_exact_match": 68.15856777493606,
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"eval_f1": 80.83131560113658,
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"eval_samples": 916,
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"train_loss": 1.1029183468903025,
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"train_runtime": 1179.7724,
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"train_samples": 14238,
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"train_samples_per_second": 24.137,
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"train_steps_per_second": 2.012
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}
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