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MiniLMv2-L6-H384_R-OCR-quality

Text Classification
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MiniLMv2-L6-H384_R-OCR-quality / README.md
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metadata
license: apache-2.0
base_model: pszemraj/MiniLMv2-L6-H384_R-fineweb-100k
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: MiniLMv2-L6-H384_R-fineweb-100k-OCR-quality-classification-cls
    results: []

MiniLMv2-L6-H384_R-fineweb-100k-OCR-quality-classification-cls

This model is a fine-tuned version of pszemraj/MiniLMv2-L6-H384_R-fineweb-100k on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0162
  • Accuracy: 0.996
  • Num Input Tokens Seen: 61536256

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

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
0.0298 0.2660 250 0.0448 0.99 8192000
0.0141 0.5321 500 0.0330 0.99 16384000
0.02 0.7981 750 0.0298 0.99 24576000
0.0085 1.0641 1000 0.0222 0.994 32765952
0.0174 1.3301 1250 0.0207 0.994 40957952
0.0104 1.5962 1500 0.0202 0.996 49149952
0.0237 1.8622 1750 0.0185 0.996 57341952

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.2.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1