winvoker/turkish-sentiment-analysis-dataset
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How to use dexter231/turkish-sentiment3 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="dexter231/turkish-sentiment3") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("dexter231/turkish-sentiment3")
model = AutoModelForSequenceClassification.from_pretrained("dexter231/turkish-sentiment3")This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on an unknown 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 | Precision | Recall | Positive F1 | Positive Precision | Positive Recall | Neutral F1 | Neutral Precision | Neutral Recall | Negative F1 | Negative Precision | Negative Recall |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2262 | 0.0290 | 200 | 0.1398 | 0.9485 | 0.9152 | 0.9084 | 0.9227 | 0.9525 | 0.9626 | 0.9426 | 0.9929 | 0.9886 | 0.9972 | 0.8003 | 0.7739 | 0.8285 |
| 0.1265 | 0.0581 | 400 | 0.1125 | 0.9590 | 0.9277 | 0.9369 | 0.9195 | 0.9626 | 0.9545 | 0.9709 | 0.9963 | 0.9961 | 0.9965 | 0.8241 | 0.8601 | 0.7910 |
| 0.1213 | 0.0871 | 600 | 0.1270 | 0.9545 | 0.9118 | 0.9573 | 0.8834 | 0.9593 | 0.9307 | 0.9896 | 0.9961 | 0.9953 | 0.9970 | 0.7801 | 0.9458 | 0.6637 |
| 0.0995 | 0.1162 | 800 | 0.1171 | 0.9606 | 0.9339 | 0.9284 | 0.9399 | 0.9636 | 0.9690 | 0.9582 | 0.9967 | 0.9979 | 0.9956 | 0.8415 | 0.8184 | 0.8660 |
| 0.108 | 0.1452 | 1000 | 0.0944 | 0.9667 | 0.9413 | 0.9513 | 0.9325 | 0.9697 | 0.9628 | 0.9768 | 0.9964 | 0.9935 | 0.9993 | 0.8578 | 0.8976 | 0.8214 |
| 0.0956 | 0.1743 | 1200 | 0.0944 | 0.9655 | 0.9418 | 0.9369 | 0.9470 | 0.9679 | 0.9738 | 0.9622 | 0.9976 | 0.9961 | 0.9991 | 0.8598 | 0.8408 | 0.8796 |
| 0.0971 | 0.2033 | 1400 | 0.0874 | 0.9688 | 0.9449 | 0.9533 | 0.9372 | 0.9713 | 0.9643 | 0.9784 | 0.9981 | 0.9978 | 0.9984 | 0.8652 | 0.8977 | 0.8349 |
| 0.0887 | 0.2324 | 1600 | 0.0876 | 0.9688 | 0.9450 | 0.9525 | 0.9381 | 0.9713 | 0.9650 | 0.9776 | 0.9981 | 0.9977 | 0.9985 | 0.8655 | 0.8947 | 0.8382 |
Base model
dbmdz/bert-base-turkish-cased