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--- |
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base_model: BAAI/bge-m3-retromae |
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tags: |
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- generated_from_trainer |
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datasets: |
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- adalbertojunior/segmentacao |
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model-index: |
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- name: test_crf |
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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_crf |
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This model is a fine-tuned version of [BAAI/bge-m3-retromae](https://huggingface.co/BAAI/bge-m3-retromae) on the adalbertojunior/segmentacao dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.0063 |
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- eval_model_preparation_time: 0.0032 |
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- eval_precision: 0.6294 |
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- eval_recall: 0.6832 |
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- eval_f1: 0.6552 |
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- eval_accuracy: 0.9989 |
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- eval_runtime: 12.8447 |
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- eval_samples_per_second: 3.893 |
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- eval_steps_per_second: 3.893 |
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- step: 0 |
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## Usage |
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```python |
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from transformers import pipeline |
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segmenter = pipeline("ner", model="./models/test_crf_v2", aggregation_strategy="simple", device=0) |
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entities = segmenter(text) |
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``` |
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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: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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: 1.0 |
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### Framework versions |
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- Transformers 4.43.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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