metadata
license: mit
base_model: microsoft/xtremedistil-l6-h256-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
datasets:
- pszemraj/OCR-quality-classification
language:
- en
xtremedistil-l6-h256-uncased: OCR-quality-classification
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:
- Loss: 0.0316
- Accuracy: 0.994
- Num Input Tokens Seen: 57341952
Intended uses & limitations
predict whether a document is clean or noisy
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2.0
Training results
| 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 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1