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End of training

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README.md ADDED
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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - emotion
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: deberta-v3-xsmall-emotion
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: emotion
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+ type: emotion
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.932
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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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+ # deberta-v3-xsmall-emotion
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the emotion dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1877
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+ - Accuracy: 0.932
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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: 3e-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: 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_steps: 500
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+ - num_epochs: 5
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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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+ | 1.3683 | 1.0 | 500 | 0.8479 | 0.6975 |
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+ | 0.547 | 2.0 | 1000 | 0.2881 | 0.905 |
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+ | 0.2378 | 3.0 | 1500 | 0.2116 | 0.925 |
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+ | 0.1704 | 4.0 | 2000 | 0.1877 | 0.932 |
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+ | 0.1392 | 5.0 | 2500 | 0.1718 | 0.9295 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.12.3
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+ - Pytorch 1.9.1
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+ - Datasets 1.15.1
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+ - Tokenizers 0.10.3
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