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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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<!-- 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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# test-finetuned__roberta-base-bne__augmented-ultrasounds-ner |
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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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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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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### Training results |
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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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### Framework versions |
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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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