community-datasets/gnad10
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How to use HAriGa/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="HAriGa/my_awesome_model") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("HAriGa/my_awesome_model")
model = AutoModelForSequenceClassification.from_pretrained("HAriGa/my_awesome_model")This model is a fine-tuned version of bert-base-german-cased on the gnad10 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 | F1 |
|---|---|---|---|---|
| 0.5884 | 1.0 | 578 | 0.3510 | 0.8940 |
| 0.2389 | 2.0 | 1156 | 0.3414 | 0.9001 |