RobZamp/sick
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How to use varun-v-rao/bert-base-cased-fp-sick with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="varun-v-rao/bert-base-cased-fp-sick") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("varun-v-rao/bert-base-cased-fp-sick")
model = AutoModelForSequenceClassification.from_pretrained("varun-v-rao/bert-base-cased-fp-sick", device_map="auto")This model is a fine-tuned version of bert-base-cased 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 | 0.6825 | 0.6727 |
| No log | 2.0 | 140 | 0.4141 | 0.8505 |
| No log | 3.0 | 210 | 0.3973 | 0.8545 |