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NER_harem_bert-large-portuguese-cased

Token Classification
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bert
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Eval Results
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  1. README.md +27 -27
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  license: mit
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- base_model: neuralmind/bert-base-portuguese-cased
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -11,7 +11,7 @@ metrics:
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  - f1
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  - accuracy
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  model-index:
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- - name: NER_harem_bert-base-portuguese-cased
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  results:
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  - task:
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  name: Token Classification
@@ -25,30 +25,30 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.6852879944482998
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  - name: Recall
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  type: recall
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- value: 0.7377661561449383
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  - name: F1
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  type: f1
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- value: 0.7105594531390537
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  - name: Accuracy
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  type: accuracy
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- value: 0.952219112355058
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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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- # NER_harem_bert-base-portuguese-cased
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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 the harem dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2351
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- - Precision: 0.6853
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- - Recall: 0.7378
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- - F1: 0.7106
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- - Accuracy: 0.9522
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  ## Model description
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@@ -79,20 +79,20 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 16 | 0.7692 | 0.0 | 0.0 | 0.0 | 0.8358 |
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- | No log | 2.0 | 32 | 0.4831 | 0.3140 | 0.2731 | 0.2921 | 0.8790 |
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- | No log | 3.0 | 48 | 0.3405 | 0.4692 | 0.4897 | 0.4793 | 0.9119 |
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- | No log | 4.0 | 64 | 0.2747 | 0.5481 | 0.6156 | 0.5799 | 0.9340 |
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- | No log | 5.0 | 80 | 0.2282 | 0.6077 | 0.6758 | 0.6399 | 0.9443 |
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- | No log | 6.0 | 96 | 0.2145 | 0.6267 | 0.6892 | 0.6565 | 0.9479 |
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- | No log | 7.0 | 112 | 0.2223 | 0.6395 | 0.6926 | 0.6650 | 0.9493 |
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- | No log | 8.0 | 128 | 0.2100 | 0.6822 | 0.7378 | 0.7089 | 0.9530 |
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- | No log | 9.0 | 144 | 0.2077 | 0.6810 | 0.7497 | 0.7137 | 0.9537 |
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- | No log | 10.0 | 160 | 0.2173 | 0.6846 | 0.7460 | 0.7140 | 0.9523 |
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- | No log | 11.0 | 176 | 0.2226 | 0.7001 | 0.7594 | 0.7285 | 0.9542 |
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- | No log | 12.0 | 192 | 0.2204 | 0.7015 | 0.7568 | 0.7281 | 0.9538 |
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- | No log | 13.0 | 208 | 0.2278 | 0.6746 | 0.7411 | 0.7063 | 0.9533 |
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- | No log | 14.0 | 224 | 0.2351 | 0.6853 | 0.7378 | 0.7106 | 0.9522 |
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  ### Framework versions
 
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  ---
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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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  datasets:
 
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  - f1
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  - accuracy
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  model-index:
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+ - name: NER_harem_bert-large-portuguese-cased
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  results:
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  - task:
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  name: Token Classification
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.7077353867693384
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  - name: Recall
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  type: recall
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+ value: 0.7553231228987672
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  - name: F1
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  type: f1
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+ value: 0.7307553306830503
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9551379448220711
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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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+ # NER_harem_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 harem dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2487
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+ - Precision: 0.7077
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+ - Recall: 0.7553
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+ - F1: 0.7308
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+ - Accuracy: 0.9551
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 16 | 0.6334 | 0.0163 | 0.0078 | 0.0106 | 0.8468 |
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+ | No log | 2.0 | 32 | 0.4537 | 0.2614 | 0.3112 | 0.2841 | 0.8826 |
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+ | No log | 3.0 | 48 | 0.3117 | 0.5262 | 0.5671 | 0.5458 | 0.9231 |
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+ | No log | 4.0 | 64 | 0.2421 | 0.5852 | 0.6631 | 0.6217 | 0.9385 |
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+ | No log | 5.0 | 80 | 0.2099 | 0.5950 | 0.6855 | 0.6370 | 0.9479 |
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+ | No log | 6.0 | 96 | 0.2153 | 0.6810 | 0.7464 | 0.7122 | 0.9551 |
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+ | No log | 7.0 | 112 | 0.2270 | 0.6894 | 0.7198 | 0.7043 | 0.9546 |
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+ | No log | 8.0 | 128 | 0.2213 | 0.6918 | 0.7437 | 0.7168 | 0.9554 |
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+ | No log | 9.0 | 144 | 0.2299 | 0.7021 | 0.7564 | 0.7283 | 0.9545 |
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+ | No log | 10.0 | 160 | 0.2256 | 0.7002 | 0.7591 | 0.7284 | 0.9562 |
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+ | No log | 11.0 | 176 | 0.2169 | 0.7100 | 0.7736 | 0.7404 | 0.9568 |
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+ | No log | 12.0 | 192 | 0.2266 | 0.6981 | 0.7740 | 0.7341 | 0.9571 |
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+ | No log | 13.0 | 208 | 0.2322 | 0.7093 | 0.7620 | 0.7347 | 0.9570 |
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+ | No log | 14.0 | 224 | 0.2487 | 0.7077 | 0.7553 | 0.7308 | 0.9551 |
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  ### Framework versions
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