universityofbucharest/laroseda
Updated • 170 • 1
How to use mateiaassAI/teacher_laroseda with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mateiaassAI/teacher_laroseda") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mateiaassAI/teacher_laroseda")
model = AutoModelForSequenceClassification.from_pretrained("mateiaassAI/teacher_laroseda")This model is a fine-tuned version of dumitrescustefan/bert-base-romanian-cased-v1 on the laroseda dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|---|
| 0.2117 | 1.0 | 688 | 0.1362 | 0.9450 | 0.9450 | 0.945 | 0.9450 | 0.945 |
| 0.1154 | 2.0 | 1376 | 0.1746 | 0.9510 | 0.9510 | 0.951 | 0.9510 | 0.951 |
Base model
dumitrescustefan/bert-base-romanian-cased-v1