stanfordnlp/imdb
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How to use gchabcou/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gchabcou/my_awesome_model") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gchabcou/my_awesome_model")
model = AutoModelForSequenceClassification.from_pretrained("gchabcou/my_awesome_model")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 | Accuracy |
|---|---|---|---|---|
| 0.2254 | 1.0 | 1563 | 0.2462 | 0.9100 |
| 0.1539 | 2.0 | 3126 | 0.2249 | 0.9326 |
Base model
distilbert/distilbert-base-uncased