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End of training

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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: judy93536/distilroberta-rbm231k-ep20-op40
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: distilroberta-rbm231k-ep20-op40-phrase5k
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # distilroberta-rbm231k-ep20-op40-phrase5k
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+
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+ This model is a fine-tuned version of [judy93536/distilroberta-rbm231k-ep20-op40](https://huggingface.co/judy93536/distilroberta-rbm231k-ep20-op40) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1681
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+ - Accuracy: 0.9560
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1.113335054745316e-06
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.28
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+ - num_epochs: 13
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 250 | 0.2748 | 0.9119 |
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+ | 0.2834 | 2.0 | 500 | 0.2418 | 0.9219 |
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+ | 0.2834 | 3.0 | 750 | 0.2013 | 0.9329 |
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+ | 0.2102 | 4.0 | 1000 | 0.1839 | 0.9389 |
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+ | 0.2102 | 5.0 | 1250 | 0.1848 | 0.9419 |
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+ | 0.1539 | 6.0 | 1500 | 0.1658 | 0.9469 |
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+ | 0.1539 | 7.0 | 1750 | 0.1685 | 0.9469 |
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+ | 0.1211 | 8.0 | 2000 | 0.1577 | 0.9550 |
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+ | 0.1211 | 9.0 | 2250 | 0.1625 | 0.9540 |
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+ | 0.1122 | 10.0 | 2500 | 0.1694 | 0.9520 |
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+ | 0.1122 | 11.0 | 2750 | 0.1583 | 0.9570 |
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+ | 0.1055 | 12.0 | 3000 | 0.1651 | 0.9570 |
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+ | 0.1055 | 13.0 | 3250 | 0.1681 | 0.9560 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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