stanfordnlp/imdb
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How to use muhtasham/finetuned-base_mini with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="muhtasham/finetuned-base_mini") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("muhtasham/finetuned-base_mini")
model = AutoModelForSequenceClassification.from_pretrained("muhtasham/finetuned-base_mini", device_map="auto")This model is a fine-tuned version of google/bert_uncased_L-4_H-256_A-4 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 |
|---|---|---|---|---|---|
| 0.354 | 2.55 | 500 | 0.2300 | 0.9116 | 0.9538 |
| 0.2086 | 5.1 | 1000 | 0.3182 | 0.8815 | 0.9370 |
| 0.1401 | 7.65 | 1500 | 0.2160 | 0.9241 | 0.9605 |
| 0.0902 | 10.2 | 2000 | 0.4684 | 0.8722 | 0.9317 |
| 0.0654 | 12.76 | 2500 | 0.4885 | 0.8747 | 0.9332 |
| 0.043 | 15.31 | 3000 | 0.3938 | 0.9076 | 0.9516 |
Base model
google/bert_uncased_L-4_H-256_A-4