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oracle_class_bin

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bert
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oracle-corejur/bert_oracle_class_bin_cur2_anno_neg_v1

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  1. README.md +15 -16
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1283
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- - Precision: 0.7996
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- - Recall: 0.8499
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- - Accuracy: 0.9627
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- - F1: 0.8240
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  ## Model description
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@@ -43,30 +43,29 @@ More information needed
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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: 16
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- - eval_batch_size: 16
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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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- - lr_scheduler_warmup_steps: 2000
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- - num_epochs: 3
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
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- | 0.1359 | 0.5606 | 1800 | 0.1183 | 0.7706 | 0.7945 | 0.9546 | 0.7824 |
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- | 0.1129 | 1.1211 | 3600 | 0.1203 | 0.7550 | 0.8529 | 0.9565 | 0.8010 |
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- | 0.0919 | 1.6817 | 5400 | 0.1111 | 0.8016 | 0.8180 | 0.9605 | 0.8098 |
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- | 0.0658 | 2.2423 | 7200 | 0.1142 | 0.8059 | 0.8249 | 0.9616 | 0.8153 |
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- | 0.0731 | 2.8029 | 9000 | 0.1283 | 0.7996 | 0.8499 | 0.9627 | 0.8240 |
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  ### Framework versions
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  - Transformers 4.41.2
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  - Pytorch 2.1.0
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- - Datasets 2.19.2
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  - Tokenizers 0.19.1
 
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  This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1746
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+ - Precision: 0.8254
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+ - Recall: 0.7923
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+ - Accuracy: 0.9615
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+ - F1: 0.8085
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  ## Model description
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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: 24
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+ - eval_batch_size: 24
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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: 5
 
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
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+ | 0.1271 | 0.8407 | 1800 | 0.1045 | 0.7513 | 0.8544 | 0.9560 | 0.7996 |
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+ | 0.0913 | 1.6815 | 3600 | 0.1075 | 0.8110 | 0.7968 | 0.9601 | 0.8038 |
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+ | 0.0791 | 2.5222 | 5400 | 0.1283 | 0.8287 | 0.7885 | 0.9615 | 0.8081 |
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+ | 0.0553 | 3.3629 | 7200 | 0.1272 | 0.8160 | 0.8067 | 0.9615 | 0.8113 |
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+ | 0.0384 | 4.2036 | 9000 | 0.1746 | 0.8254 | 0.7923 | 0.9615 | 0.8085 |
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  ### Framework versions
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  - Transformers 4.41.2
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  - Pytorch 2.1.0
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+ - Datasets 2.20.0
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  - Tokenizers 0.19.1
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