fever/fever
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How to use ernlavr/destilbert_fever_nli with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="ernlavr/destilbert_fever_nli") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("ernlavr/destilbert_fever_nli")
model = AutoModelForSequenceClassification.from_pretrained("ernlavr/destilbert_fever_nli")This model is a fine-tuned version of distilbert-base-cased on an unknown 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 | F1 |
|---|---|---|---|---|
| No log | 1.0 | 235 | 1.2711 | 0.6671 |
| No log | 2.0 | 470 | 1.8000 | 0.6538 |
| 0.1341 | 3.0 | 705 | 1.6965 | 0.6770 |
| 0.1341 | 4.0 | 940 | 1.8415 | 0.6619 |
| 0.068 | 5.0 | 1175 | 1.7477 | 0.6682 |
| 0.068 | 6.0 | 1410 | 2.2007 | 0.6695 |
| 0.0435 | 7.0 | 1645 | 2.3327 | 0.6705 |
| 0.0435 | 8.0 | 1880 | 2.3927 | 0.6729 |
| 0.015 | 9.0 | 2115 | 2.4978 | 0.6721 |
| 0.015 | 10.0 | 2350 | 2.5463 | 0.6747 |
Base model
distilbert/distilbert-base-cased