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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: microsoft/deberta-v3-base
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: mdeberta-domain_EN_fold2
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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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+ # mdeberta-domain_EN_fold2
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4394
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+ - Accuracy: 0.8207
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+ - Precision: 0.7590
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+ - Recall: 0.7755
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+ - F1: 0.7645
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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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 | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 1.0408 | 1.0 | 19 | 0.8182 | 0.5931 | 0.8644 | 0.3333 | 0.2482 |
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+ | 0.7383 | 2.0 | 38 | 0.6728 | 0.5931 | 0.8644 | 0.3333 | 0.2482 |
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+ | 0.6381 | 3.0 | 57 | 0.6066 | 0.7862 | 0.8283 | 0.6696 | 0.6001 |
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+ | 0.5638 | 4.0 | 76 | 0.5272 | 0.7931 | 0.7363 | 0.6804 | 0.6422 |
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+ | 0.4701 | 5.0 | 95 | 0.4757 | 0.7931 | 0.7324 | 0.6811 | 0.6138 |
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+ | 0.4087 | 6.0 | 114 | 0.4957 | 0.8 | 0.7199 | 0.6911 | 0.6670 |
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+ | 0.3438 | 7.0 | 133 | 0.5317 | 0.7862 | 0.7128 | 0.6673 | 0.6757 |
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+ | 0.281 | 8.0 | 152 | 0.4456 | 0.8069 | 0.7325 | 0.7532 | 0.7376 |
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+ | 0.2428 | 9.0 | 171 | 0.4442 | 0.8069 | 0.7445 | 0.7677 | 0.7540 |
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+ | 0.2166 | 10.0 | 190 | 0.4394 | 0.8207 | 0.7590 | 0.7755 | 0.7645 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.0
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+ - Pytorch 2.3.1
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+ - Datasets 2.21.0
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+ - Tokenizers 0.20.1
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