stanfordnlp/imdb
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How to use dfurman/deberta-v3-large-imdb-v0.1 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="dfurman/deberta-v3-large-imdb-v0.1") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("dfurman/deberta-v3-large-imdb-v0.1")
model = AutoModelForSequenceClassification.from_pretrained("dfurman/deberta-v3-large-imdb-v0.1", device_map="auto")This model is a fine-tuned version of microsoft/deberta-v3-large on the imdb 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.2471 | 1.0 | 3125 | 0.2004 | 0.9487 | 0.9474 | 0.9710 | 0.9250 |
| 0.2029 | 2.0 | 6250 | 0.1715 | 0.9603 | 0.9600 | 0.9664 | 0.9537 |
| 0.0631 | 3.0 | 9375 | 0.2049 | 0.9566 | 0.9555 | 0.9793 | 0.9329 |
| 0.0432 | 4.0 | 12500 | 0.1906 | 0.9646 | 0.9645 | 0.9679 | 0.9610 |
Base model
microsoft/deberta-v3-large