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@@ -22,27 +22,27 @@ This repository contains a model trained to predict Common European Framework of
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  - Model architecture: BERT (base model: `bert-base-...`)
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  - Task: CEFR level prediction for text classification
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  - Training dataset: CEFR dataset
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- - Fine-tuning: Epochs, Loss, Accuracy, etc.
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  ## Performance
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  The model's performance during training is summarized below:
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- | Epoch | Training Loss | Validation Loss
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- |-------|---------------|-----------------
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- | 1 | 0.350600 | 0.400248
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- | 2 | 0.300800 | 0.449286
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- | 3 | 0.218800 | 0.510898
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- | 4 | 0.150300 | 0.599973
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- | 5 | 0.099000 | 0.678500
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- Additional metrics:
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- - Training Loss: 0.22364403076171874
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- - Training Runtime: 5274.6105 seconds
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- - Training Samples per Second: 1.303
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- - Total Floating Point Operations: 1.4498992298262528e+16
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  ## Usage
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  - Model architecture: BERT (base model: `bert-base-...`)
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  - Task: CEFR level prediction for text classification
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  - Training dataset: CEFR dataset
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+ - Fine-tuning: Epochs, Loss, etc.
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  ## Performance
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  The model's performance during training is summarized below:
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+ | Epoch | Training Loss | Validation Loss |
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+ |-------|---------------|-----------------|
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+ | 1 | 0.412300 | 0.396337 |
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+ | 2 | 0.369600 | 0.388866 |
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+ | 3 | 0.298200 | 0.419018 |
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+ | 4 | 0.214500 | 0.481886 |
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+ | 5 | 0.148300 | 0.557343 |
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+ --Additional metrics:
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+ --Training Loss: 0.2900624789151278
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+ --Training Runtime: 5168.3962 seconds
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+ --Training Samples per Second: 10.642
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+ --Total Floating Point Operations: 1.447162776576e+16
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  ## Usage
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