defunct-datasets/amazon_reviews_multi
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How to use philschmid/distilbert-base-multilingual-cased-sentiment-2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="philschmid/distilbert-base-multilingual-cased-sentiment-2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("philschmid/distilbert-base-multilingual-cased-sentiment-2")
model = AutoModelForSequenceClassification.from_pretrained("philschmid/distilbert-base-multilingual-cased-sentiment-2")This model is a fine-tuned version of distilbert-base-multilingual-cased 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 |
|---|---|---|---|---|---|
| 0.6885 | 0.53 | 5000 | 0.6532 | 0.7217 | 0.7217 |
| 0.6411 | 1.07 | 10000 | 0.6348 | 0.7319 | 0.7319 |
| 0.6057 | 1.6 | 15000 | 0.6186 | 0.7387 | 0.7387 |
| 0.5844 | 2.13 | 20000 | 0.6236 | 0.7449 | 0.7449 |
| 0.549 | 2.67 | 25000 | 0.6067 | 0.7476 | 0.7476 |