rajpurkar/squad
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How to use HaythamB/distilbert-base-uncased-finetuned-squad with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="HaythamB/distilbert-base-uncased-finetuned-squad") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("HaythamB/distilbert-base-uncased-finetuned-squad")
model = AutoModelForQuestionAnswering.from_pretrained("HaythamB/distilbert-base-uncased-finetuned-squad")This model is a fine-tuned version of distilbert-base-uncased on the squad dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6775 | 0.23 | 500 | 1.5964 |
| 1.6083 | 0.45 | 1000 | 1.3869 |
| 1.4495 | 0.68 | 1500 | 1.2649 |
| 1.3425 | 0.9 | 2000 | 1.2112 |
| 1.2108 | 1.13 | 2500 | 1.1996 |
| 1.1106 | 1.36 | 3000 | 1.1464 |
| 1.0877 | 1.58 | 3500 | 1.1472 |
| 1.0493 | 1.81 | 4000 | 1.1132 |
| 1.0196 | 2.03 | 4500 | 1.1237 |
| 0.8958 | 2.26 | 5000 | 1.1212 |
| 0.9042 | 2.48 | 5500 | 1.1219 |
| 0.8821 | 2.71 | 6000 | 1.1013 |
| 0.8943 | 2.94 | 6500 | 1.1010 |
Base model
distilbert/distilbert-base-uncased