defunct-datasets/amazon_reviews_multi
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How to use d4niel92/xlm-roberta-base-finetuned-marc-en with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="d4niel92/xlm-roberta-base-finetuned-marc-en") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("d4niel92/xlm-roberta-base-finetuned-marc-en")
model = AutoModelForSequenceClassification.from_pretrained("d4niel92/xlm-roberta-base-finetuned-marc-en", device_map="auto")This model is a fine-tuned version of xlm-roberta-base 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 | Mae |
|---|---|---|---|---|
| 1.092 | 1.0 | 235 | 0.9514 | 0.5122 |
| 0.9509 | 2.0 | 470 | 0.8976 | 0.4268 |
Base model
FacebookAI/xlm-roberta-base