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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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+ 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: roberta-base_auditor_sentiment
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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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+ # roberta-base_auditor_sentiment
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5356
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+ - Accuracy: 0.8554
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+ - Precision: 0.8224
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+ - Recall: 0.8722
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+ - F1: 0.8414
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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-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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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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+
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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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+ | 0.4217 | 1.0 | 485 | 0.6358 | 0.8223 | 0.8142 | 0.8135 | 0.8134 |
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+ | 0.6538 | 2.0 | 970 | 0.6491 | 0.8388 | 0.8584 | 0.8025 | 0.8192 |
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+ | 0.3961 | 3.0 | 1455 | 0.5356 | 0.8554 | 0.8224 | 0.8722 | 0.8414 |
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+ | 0.1121 | 4.0 | 1940 | 0.7393 | 0.8512 | 0.8414 | 0.8477 | 0.8428 |
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+ | 0.0192 | 5.0 | 2425 | 0.7233 | 0.8698 | 0.8581 | 0.8743 | 0.8657 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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