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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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+ base_model: microsoft/deberta-v3-xsmall
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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: deberta-v3-xsmall-zeroshot-v1.1-none
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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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+ # deberta-v3-xsmall-zeroshot-v1.1-none
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2072
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+ - F1 Macro: 0.6369
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+ - F1 Micro: 0.7013
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+ - Accuracy Balanced: 0.6751
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+ - Accuracy: 0.7013
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+ - Precision Macro: 0.6439
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+ - Recall Macro: 0.6751
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+ - Precision Micro: 0.7013
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+ - Recall Micro: 0.7013
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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: 128
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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: 0.06
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------------:|:--------:|:---------------:|:------------:|:---------------:|:------------:|
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+ | 0.2532 | 1.0 | 30790 | 0.4006 | 0.8198 | 0.8384 | 0.8151 | 0.8384 | 0.8257 | 0.8151 | 0.8384 | 0.8384 |
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+ | 0.2113 | 2.0 | 61580 | 0.3907 | 0.8254 | 0.8439 | 0.8198 | 0.8439 | 0.8326 | 0.8198 | 0.8439 | 0.8439 |
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+ | 0.1727 | 3.0 | 92370 | 0.4228 | 0.8306 | 0.8461 | 0.8297 | 0.8461 | 0.8315 | 0.8297 | 0.8461 | 0.8461 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.3
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+ - Pytorch 2.1.2+cu121
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+ - Datasets 2.14.7
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+ - Tokenizers 0.13.3
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+ "_name_or_path": "microsoft/deberta-v3-xsmall",
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+ "DebertaV2ForSequenceClassification"
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