stanfordnlp/imdb
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How to use Sif10/my_awesome_model_imdb with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Sif10/my_awesome_model_imdb") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Sif10/my_awesome_model_imdb")
model = AutoModelForSequenceClassification.from_pretrained("Sif10/my_awesome_model_imdb")This model is a fine-tuned version of distilbert/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 | Accuracy |
|---|---|---|---|---|
| 0.4013 | 1.0 | 782 | 0.3535 | 0.8445 |
| 0.2107 | 2.0 | 1564 | 0.3589 | 0.8550 |
| 0.1158 | 3.0 | 2346 | 0.5241 | 0.8576 |
| 0.0423 | 4.0 | 3128 | 0.7881 | 0.8545 |
| 0.0238 | 5.0 | 3910 | 0.7781 | 0.8591 |
Base model
distilbert/distilbert-base-uncased