stanfordnlp/imdb
Viewer • Updated • 100k • 178k • 370
How to use ttwj-sutd/finetuning-sentiment-model-3000-samples-5pm with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="ttwj-sutd/finetuning-sentiment-model-3000-samples-5pm") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ttwj-sutd/finetuning-sentiment-model-3000-samples-5pm")
model = AutoModelForSequenceClassification.from_pretrained("ttwj-sutd/finetuning-sentiment-model-3000-samples-5pm")This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 188 | 0.3858 | 0.84 |
| No log | 2.0 | 376 | 0.3146 | 0.8833 |
| 0.2573 | 3.0 | 564 | 0.3938 | 0.8833 |
| 0.2573 | 4.0 | 752 | 0.4325 | 0.88 |