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End of training

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README.md ADDED
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+ ---
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+ base_model: manucos/finetuned__roberta-base-bne__augmented-ultrasounds
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: test-finetuned__roberta-base-bne__augmented-ultrasounds-ner
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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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+ # test-finetuned__roberta-base-bne__augmented-ultrasounds-ner
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+
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+ This model is a fine-tuned version of [manucos/finetuned__roberta-base-bne__augmented-ultrasounds](https://huggingface.co/manucos/finetuned__roberta-base-bne__augmented-ultrasounds) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3332
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+ - Precision: 0.7926
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+ - Recall: 0.8856
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+ - F1: 0.8365
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+ - Accuracy: 0.9236
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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: 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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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 206 | 0.2753 | 0.7460 | 0.8411 | 0.7907 | 0.9106 |
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+ | No log | 2.0 | 412 | 0.2692 | 0.7770 | 0.8603 | 0.8165 | 0.9238 |
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+ | 0.2993 | 3.0 | 618 | 0.3276 | 0.7493 | 0.8472 | 0.7952 | 0.9087 |
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+ | 0.2993 | 4.0 | 824 | 0.2983 | 0.7847 | 0.8704 | 0.8253 | 0.9180 |
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+ | 0.054 | 5.0 | 1030 | 0.3066 | 0.7852 | 0.8806 | 0.8302 | 0.9221 |
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+ | 0.054 | 6.0 | 1236 | 0.3211 | 0.7652 | 0.8806 | 0.8188 | 0.9211 |
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+ | 0.054 | 7.0 | 1442 | 0.3314 | 0.7883 | 0.8704 | 0.8273 | 0.9189 |
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+ | 0.0205 | 8.0 | 1648 | 0.3245 | 0.7827 | 0.8785 | 0.8278 | 0.9224 |
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+ | 0.0205 | 9.0 | 1854 | 0.3306 | 0.7825 | 0.8846 | 0.8304 | 0.9235 |
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+ | 0.0128 | 10.0 | 2060 | 0.3332 | 0.7926 | 0.8856 | 0.8365 | 0.9236 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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