stanfordnlp/snli
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How to use varun-v-rao/gpt2-large-lora-2.95M-snli-model2 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="varun-v-rao/gpt2-large-lora-2.95M-snli-model2") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("varun-v-rao/gpt2-large-lora-2.95M-snli-model2")
model = AutoModelForSequenceClassification.from_pretrained("varun-v-rao/gpt2-large-lora-2.95M-snli-model2", device_map="auto")This model is a fine-tuned version of openai-community/gpt2-large on the snli 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 |
|---|---|---|---|---|
| 0.4344 | 1.0 | 4292 | 0.3571 | 0.8650 |
| 0.402 | 2.0 | 8584 | 0.3363 | 0.8744 |
| 0.3958 | 3.0 | 12876 | 0.3280 | 0.8767 |
Base model
openai-community/gpt2-large