End of training
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README.md
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---
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license: mit
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base_model: neuralmind/bert-
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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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model-index:
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- name: LVI_bert-
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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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# LVI_bert-
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This model is a fine-tuned version of [neuralmind/bert-
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- F1: 0.
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- Precision: 0.
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- Recall: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.17 | 5.0 | 16085 | 0.2393 | 0.9428 | 0.9445 | 0.9182 | 0.9723 |
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### Framework versions
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license: mit
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base_model: neuralmind/bert-large-portuguese-cased
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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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model-index:
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- name: LVI_bert-large-portuguese-cased
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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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# LVI_bert-large-portuguese-cased
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This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6945
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- Accuracy: 0.5
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- F1: 0.0
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- Precision: 0.0
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- Recall: 0.0
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.2141 | 1.0 | 3217 | 0.2055 | 0.9405 | 0.9423 | 0.9140 | 0.9724 |
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| 0.7115 | 2.0 | 6434 | 0.6959 | 0.5 | 0.0 | 0.0 | 0.0 |
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| 0.7041 | 3.0 | 9651 | 0.6931 | 0.5 | 0.0 | 0.0 | 0.0 |
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| 0.7056 | 4.0 | 12868 | 0.6945 | 0.5 | 0.0 | 0.0 | 0.0 |
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### Framework versions
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model.safetensors
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