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How to use kislayashresthavk/test_trainer with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="kislayashresthavk/test_trainer") # pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("kislayashresthavk/test_trainer")
model = AutoModelForSequenceClassification.from_pretrained("kislayashresthavk/test_trainer", device_map="auto")This model is a fine-tuned version of distilbert-base-uncased 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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 125 | 1.0360 | 0.55 |
| No log | 2.0 | 250 | 0.9844 | 0.588 |
| No log | 3.0 | 375 | 0.9986 | 0.602 |
Base model
distilbert/distilbert-base-uncased