RobZamp/sick
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How to use varun-v-rao/opt-1.3b-fp-sick with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="varun-v-rao/opt-1.3b-fp-sick") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("varun-v-rao/opt-1.3b-fp-sick")
model = AutoModelForSequenceClassification.from_pretrained("varun-v-rao/opt-1.3b-fp-sick")This model is a fine-tuned version of facebook/opt-1.3b on the sick 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 | 70 | 0.3555 | 0.8828 |
| No log | 2.0 | 140 | 0.3348 | 0.8848 |
| No log | 3.0 | 210 | 0.4505 | 0.8889 |
Base model
facebook/opt-1.3b