stanfordnlp/imdb
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How to use Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert")
model = AutoModelForSequenceClassification.from_pretrained("Godspower/finetuned-sentiment-analysis-model-3000-samples-base-distilbert", device_map="auto")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:
Base model
distilbert/distilbert-base-uncased