stanfordnlp/imdb
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How to use yuqinA/model_trained with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="yuqinA/model_trained") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("yuqinA/model_trained")
model = AutoModelForSequenceClassification.from_pretrained("yuqinA/model_trained", device_map="auto")This model is a fine-tuned version of distilbert/distilbert-base-uncased on an 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 | Accuracy |
|---|---|---|---|---|
| 0.2215 | 1.0 | 1563 | 0.1986 | 0.9239 |
| 0.1482 | 2.0 | 3126 | 0.2313 | 0.9308 |
Base model
distilbert/distilbert-base-uncased