pszemraj/OCR-quality-classification
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How to use pszemraj/xtremedistil-l6-h256-OCR-quality with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="pszemraj/xtremedistil-l6-h256-OCR-quality") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("pszemraj/xtremedistil-l6-h256-OCR-quality")
model = AutoModelForSequenceClassification.from_pretrained("pszemraj/xtremedistil-l6-h256-OCR-quality", device_map="auto")This model is a fine-tuned version of microsoft/xtremedistil-l6-h256-uncased on pszemraj/OCR-quality-classification
It achieves the following results on the evaluation set:
predict whether a document is clean or noisy
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Input Tokens Seen |
|---|---|---|---|---|---|
| 0.0812 | 0.2660 | 250 | 0.0860 | 0.986 | 8192000 |
| 0.0637 | 0.5321 | 500 | 0.0532 | 0.988 | 16384000 |
| 0.031 | 0.7981 | 750 | 0.0463 | 0.99 | 24576000 |
| 0.0315 | 1.0641 | 1000 | 0.0343 | 0.992 | 32765952 |
| 0.0223 | 1.3301 | 1250 | 0.0337 | 0.994 | 40957952 |
| 0.0137 | 1.5962 | 1500 | 0.0423 | 0.99 | 49149952 |
| 0.0186 | 1.8622 | 1750 | 0.0316 | 0.994 | 57341952 |
Base model
microsoft/xtremedistil-l6-h256-uncased