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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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datasets: |
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- adalbertojunior/entities |
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model-index: |
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- name: test_v4 |
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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_v4 |
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This model is a fine-tuned version of [./models/entities/test_v4](https://huggingface.co/./models/entities/test_v4) on the adalbertojunior/entities dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 0.1648 |
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- eval_model_preparation_time: 0.0009 |
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- eval_precision: 0.8411 |
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- eval_recall: 0.8900 |
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- eval_f1: 0.8649 |
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- eval_accuracy: 0.9744 |
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- eval_runtime: 177.3832 |
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- eval_samples_per_second: 27.962 |
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- eval_steps_per_second: 27.962 |
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- step: 0 |
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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: 0.0002 |
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- train_batch_size: 8 |
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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: 64 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 20.0 |
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### Testset Results |
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| Label | Precision | Recall | F1-Score | Support | |
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|---------------------|-----------|--------|----------|---------| |
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| ATRIBUICAO | 0.82 | 0.82 | 0.82 | 221 | |
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| DECISAO | 0.81 | 0.82 | 0.82 | 544 | |
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| FUNCAO | 0.94 | 0.89 | 0.91 | 486 | |
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| FUNDAMENTO | 0.89 | 0.83 | 0.86 | 1501 | |
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| LOCAL | 0.85 | 0.84 | 0.85 | 245 | |
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| ORGANIZACAO | 0.90 | 0.86 | 0.88 | 626 | |
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| PEDIDO | 0.86 | 0.81 | 0.83 | 4341 | |
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| PESSOA | 0.95 | 0.94 | 0.95 | 654 | |
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| REFLEXO | 0.85 | 0.84 | 0.85 | 358 | |
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| TIPO_ACAO | 0.93 | 0.89 | 0.91 | 341 | |
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| TRIBUNAL | 0.96 | 0.92 | 0.94 | 190 | |
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| VALOR_ACORDO | 0.91 | 0.71 | 0.79 | 41 | |
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| VALOR_CAUSA | 0.89 | 0.92 | 0.90 | 62 | |
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| VALOR_CONDENACAO | 0.89 | 0.76 | 0.82 | 72 | |
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| VALOR_CUSTAS | 0.95 | 0.93 | 0.94 | 134 | |
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| VALOR_PEDIDO | 0.94 | 0.81 | 0.87 | 308 | |
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| VARA | 0.95 | 0.96 | 0.96 | 81 | |
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| **micro avg** | 0.88 | 0.84 | 0.86 | 10205 | |
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| **macro avg** | 0.90 | 0.86 | 0.88 | 10205 | |
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| **weighted avg** | 0.88 | 0.84 | 0.86 | 10205 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.21.0 |
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