stanfordnlp/sst2
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How to use kowsiknd/bert-base-uncased-sst2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="kowsiknd/bert-base-uncased-sst2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("kowsiknd/bert-base-uncased-sst2")
model = AutoModelForSequenceClassification.from_pretrained("kowsiknd/bert-base-uncased-sst2")This model is a fine-tuned version of bert-base-uncased on the sst2 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 | 125 | 1.0209 | 0.836 |
| No log | 2.0 | 250 | 1.0430 | 0.85 |
| No log | 3.0 | 375 | 0.9312 | 0.876 |