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nees-bert-base-portuguese-cased-finetuned-ner

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  1. README.md +23 -18
  2. model.safetensors +1 -1
  3. runs/Mar02_00-36-55_4b3192fc8cc0/events.out.tfevents.1709339823.4b3192fc8cc0.599.0 +2 -2
  4. runs/Mar02_00-36-55_4b3192fc8cc0/events.out.tfevents.1709347950.4b3192fc8cc0.599.1 +3 -0
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: 0.0255
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- - Precision: 0.6545
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- - Recall: 0.7802
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- - F1: 0.7119
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- - Accuracy: 0.9952
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  ## Model description
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@@ -49,27 +49,32 @@ The following hyperparameters were used during training:
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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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- | 0.0344 | 1.0 | 519 | 0.0189 | 0.0 | 0.0 | 0.0 | 0.9949 |
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- | 0.0145 | 2.0 | 1038 | 0.0112 | 0.5050 | 0.4737 | 0.4888 | 0.9952 |
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- | 0.0121 | 3.0 | 1557 | 0.0132 | 0.3684 | 0.1300 | 0.1922 | 0.9953 |
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- | 0.0107 | 4.0 | 2076 | 0.0239 | 0.6366 | 0.7647 | 0.6948 | 0.9955 |
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- | 0.0056 | 5.0 | 2595 | 0.0151 | 0.6845 | 0.7121 | 0.6980 | 0.9950 |
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- | 0.0053 | 6.0 | 3114 | 0.0278 | 0.6432 | 0.7368 | 0.6869 | 0.9943 |
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- | 0.0047 | 7.0 | 3633 | 0.0199 | 0.5682 | 0.7740 | 0.6553 | 0.9953 |
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- | 0.0043 | 8.0 | 4152 | 0.0231 | 0.6429 | 0.7802 | 0.7049 | 0.9951 |
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- | 0.0022 | 9.0 | 4671 | 0.0255 | 0.6487 | 0.7833 | 0.7097 | 0.9955 |
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- | 0.0025 | 10.0 | 5190 | 0.0255 | 0.6545 | 0.7802 | 0.7119 | 0.9952 |
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.17.1
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  - Tokenizers 0.15.2
 
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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: 0.0360
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+ - Precision: 0.5404
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+ - Recall: 0.7230
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+ - F1: 0.6185
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+ - Accuracy: 0.9949
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  ## Model description
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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: 15
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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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+ | 0.0352 | 1.0 | 599 | 0.0212 | 0.0154 | 0.0034 | 0.0055 | 0.9956 |
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+ | 0.0125 | 2.0 | 1198 | 0.0184 | 0.4039 | 0.2770 | 0.3287 | 0.9958 |
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+ | 0.0099 | 3.0 | 1797 | 0.0141 | 0.4528 | 0.4865 | 0.4691 | 0.9958 |
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+ | 0.0082 | 4.0 | 2396 | 0.0279 | 0.4558 | 0.5743 | 0.5082 | 0.9958 |
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+ | 0.0074 | 5.0 | 2995 | 0.0138 | 0.5153 | 0.6824 | 0.5872 | 0.9960 |
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+ | 0.0034 | 6.0 | 3594 | 0.0193 | 0.4934 | 0.6284 | 0.5527 | 0.9953 |
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+ | 0.0046 | 7.0 | 4193 | 0.0190 | 0.5305 | 0.7635 | 0.6260 | 0.9960 |
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+ | 0.0024 | 8.0 | 4792 | 0.0286 | 0.5670 | 0.6858 | 0.6208 | 0.9955 |
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+ | 0.0024 | 9.0 | 5391 | 0.0270 | 0.5889 | 0.5709 | 0.5798 | 0.9953 |
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+ | 0.0034 | 10.0 | 5990 | 0.0339 | 0.5623 | 0.6858 | 0.6180 | 0.9953 |
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+ | 0.0015 | 11.0 | 6589 | 0.0373 | 0.6122 | 0.7095 | 0.6573 | 0.9947 |
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+ | 0.001 | 12.0 | 7188 | 0.0361 | 0.5519 | 0.6284 | 0.5877 | 0.9950 |
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+ | 0.0005 | 13.0 | 7787 | 0.0353 | 0.5658 | 0.6824 | 0.6187 | 0.9950 |
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+ | 0.0007 | 14.0 | 8386 | 0.0355 | 0.5556 | 0.7264 | 0.6296 | 0.9948 |
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+ | 0.0003 | 15.0 | 8985 | 0.0360 | 0.5404 | 0.7230 | 0.6185 | 0.9949 |
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  ### Framework versions
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+ - Transformers 4.38.1
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.18.0
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  - Tokenizers 0.15.2
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