clinc/clinc_oos
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How to use susnato/finetuned_ckpt with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="susnato/finetuned_ckpt") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("susnato/finetuned_ckpt")
model = AutoModelForSequenceClassification.from_pretrained("susnato/finetuned_ckpt")This model is a fine-tuned version of distilbert-base-uncased on the clinc_oos 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 |
|---|---|---|---|---|
| No log | 1.0 | 318 | 3.2814 | 0.7410 |
| 3.783 | 2.0 | 636 | 1.8740 | 0.8335 |
| 3.783 | 3.0 | 954 | 1.1590 | 0.8916 |
| 1.6892 | 4.0 | 1272 | 0.8595 | 0.9103 |
| 0.9052 | 5.0 | 1590 | 0.7767 | 0.9161 |