google/xtreme
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How to use samuelrince/bert-base-cased-finetuned-panx-en with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("token-classification", model="samuelrince/bert-base-cased-finetuned-panx-en") # Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("samuelrince/bert-base-cased-finetuned-panx-en")
model = AutoModelForTokenClassification.from_pretrained("samuelrince/bert-base-cased-finetuned-panx-en", device_map="auto")This model is a fine-tuned version of bert-base-cased on the xtreme 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 |
|---|---|---|---|
| 0.2941 | 1.0 | 1250 | 0.2432 |
| 0.186 | 2.0 | 2500 | 0.2214 |
| 0.1387 | 3.0 | 3750 | 0.2478 |