rajpurkar/squad
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How to use prudhvirazz/google-flan-t5-small-modified_v2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("question-answering", model="prudhvirazz/google-flan-t5-small-modified_v2") # Load model directly
from transformers import AutoTokenizer, AutoModelForQuestionAnswering
tokenizer = AutoTokenizer.from_pretrained("prudhvirazz/google-flan-t5-small-modified_v2")
model = AutoModelForQuestionAnswering.from_pretrained("prudhvirazz/google-flan-t5-small-modified_v2", device_map="auto")This model is a fine-tuned version of google/flan-t5-small 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 |
|---|---|---|---|
| No log | 1.0 | 250 | 3.7751 |
| 4.3074 | 2.0 | 500 | 2.1221 |
| 4.3074 | 3.0 | 750 | 1.7130 |
| 2.5366 | 4.0 | 1000 | 1.5271 |
| 2.5366 | 5.0 | 1250 | 1.4301 |
| 2.0483 | 6.0 | 1500 | 1.3643 |
| 2.0483 | 7.0 | 1750 | 1.3389 |
| 1.8774 | 8.0 | 2000 | 1.3123 |
| 1.8774 | 9.0 | 2250 | 1.3067 |
| 1.7724 | 10.0 | 2500 | 1.3020 |
Base model
google/flan-t5-small