stanfordnlp/imdb
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How to use shed-e/MLM with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="shed-e/MLM") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("shed-e/MLM")
model = AutoModelForMaskedLM.from_pretrained("shed-e/MLM")This model is a fine-tuned version of distilbert-base-uncased on the imdb 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 |
|---|---|---|---|
| 2.6954 | 1.0 | 157 | 2.5243 |
| 2.563 | 2.0 | 314 | 2.4738 |
| 2.5258 | 3.0 | 471 | 2.4369 |