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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: roberta-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: htk-aes-2
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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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+ # htk-aes-2
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8348
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+ - Qwk: 0.7851
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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: 5e-06
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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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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Qwk |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 303 | 0.9556 | 0.6966 |
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+ | 1.1107 | 2.0 | 606 | 0.8401 | 0.7658 |
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+ | 1.1107 | 3.0 | 909 | 0.8261 | 0.7804 |
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+ | 0.8616 | 4.0 | 1212 | 0.8239 | 0.7896 |
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+ | 0.8084 | 5.0 | 1515 | 0.8348 | 0.7851 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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