nyu-mll/glue
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How to use gokuls/sa_BERT_24_cola with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="gokuls/sa_BERT_24_cola") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("gokuls/sa_BERT_24_cola")
model = AutoModelForSequenceClassification.from_pretrained("gokuls/sa_BERT_24_cola")This model is a fine-tuned version of gokuls/bert_base_24 on the GLUE COLA 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 | Matthews Correlation | Accuracy |
|---|---|---|---|---|---|
| 0.6138 | 1.0 | 90 | 0.6120 | 0.0 | 0.6913 |
| 0.5898 | 2.0 | 180 | 0.6242 | 0.0656 | 0.6932 |
| 0.5491 | 3.0 | 270 | 0.6798 | 0.0733 | 0.6405 |
| 0.5027 | 4.0 | 360 | 0.6873 | 0.0667 | 0.6328 |
| 0.4549 | 5.0 | 450 | 0.7841 | 0.1025 | 0.6299 |
| 0.4177 | 6.0 | 540 | 0.8221 | 0.0827 | 0.5849 |