defunct-datasets/amazon_reviews_multi
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How to use santiviquez/amazon-reviews-finetuning-distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="santiviquez/amazon-reviews-finetuning-distilbert-base-uncased") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("santiviquez/amazon-reviews-finetuning-distilbert-base-uncased")
model = AutoModelForSequenceClassification.from_pretrained("santiviquez/amazon-reviews-finetuning-distilbert-base-uncased")This model is a fine-tuned version of nlptown/bert-base-multilingual-uncased-sentiment on the amazon_reviews_multi 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 | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 188 | 0.5587 | 0.7756 | 0.7297 |
| No log | 2.0 | 376 | 0.5859 | 0.7703 | 0.7271 |