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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-small
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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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: DeBERTaV3_model_V5
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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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+ # DeBERTaV3_model_V5
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+
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+ This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1164
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+ - Accuracy: 0.9652
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+ - F1: 0.8192
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+ - Precision: 0.8524
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+ - Recall: 0.7885
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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: 5
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+ - eval_batch_size: 5
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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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+ - num_epochs: 12
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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 | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 1.0 | 182 | 0.2809 | 0.9 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 364 | 0.2176 | 0.9216 | 0.4027 | 0.8451 | 0.2643 |
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+ | 0.2842 | 3.0 | 546 | 0.1558 | 0.9493 | 0.7074 | 0.8373 | 0.6123 |
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+ | 0.2842 | 4.0 | 728 | 0.1302 | 0.9568 | 0.7742 | 0.8116 | 0.7401 |
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+ | 0.2842 | 5.0 | 910 | 0.1164 | 0.9652 | 0.8192 | 0.8524 | 0.7885 |
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+ | 0.1025 | 6.0 | 1092 | 0.1193 | 0.9634 | 0.8135 | 0.8303 | 0.7974 |
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+ | 0.1025 | 7.0 | 1274 | 0.1242 | 0.9648 | 0.8214 | 0.8326 | 0.8106 |
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+ | 0.1025 | 8.0 | 1456 | 0.1266 | 0.9626 | 0.8098 | 0.8227 | 0.7974 |
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+ | 0.0376 | 9.0 | 1638 | 0.1259 | 0.9648 | 0.8206 | 0.8356 | 0.8062 |
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+ | 0.0376 | 10.0 | 1820 | 0.1269 | 0.9661 | 0.8285 | 0.8378 | 0.8194 |
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+ | 0.023 | 11.0 | 2002 | 0.1290 | 0.9661 | 0.8293 | 0.8348 | 0.8238 |
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+ | 0.023 | 12.0 | 2184 | 0.1312 | 0.9630 | 0.8150 | 0.8150 | 0.8150 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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+ "layer_norm_eps": 1e-07,
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