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NER_harem_bert-base-portuguese-cased

Token Classification
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bert
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  1. README.md +25 -27
  2. model.safetensors +1 -1
README.md CHANGED
@@ -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: harem-ner
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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: 0.6869415807560137
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  - name: Recall
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  type: recall
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- value: 0.7467314157639149
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  - name: F1
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  type: f1
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- value: 0.7155897619473779
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  - name: Accuracy
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  type: accuracy
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- value: 0.9527588964414234
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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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- # harem-ner
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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: 0.2411
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- - Precision: 0.6869
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- - Recall: 0.7467
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- - F1: 0.7156
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- - Accuracy: 0.9528
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  ## Model description
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@@ -79,22 +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 | 0.7683 | 0.0 | 0.0 | 0.0 | 0.8358 |
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- | No log | 2.0 | 32 | 0.4727 | 0.3375 | 0.2955 | 0.3151 | 0.8803 |
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- | No log | 3.0 | 48 | 0.3498 | 0.4859 | 0.4838 | 0.4848 | 0.9090 |
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- | No log | 4.0 | 64 | 0.2771 | 0.5651 | 0.6223 | 0.5924 | 0.9354 |
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- | No log | 5.0 | 80 | 0.2309 | 0.5901 | 0.6743 | 0.6294 | 0.9424 |
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- | No log | 6.0 | 96 | 0.2195 | 0.6229 | 0.6997 | 0.6590 | 0.9469 |
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- | No log | 7.0 | 112 | 0.2151 | 0.6239 | 0.6903 | 0.6554 | 0.9480 |
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- | No log | 8.0 | 128 | 0.2178 | 0.6682 | 0.7236 | 0.6948 | 0.9504 |
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- | No log | 9.0 | 144 | 0.2210 | 0.6808 | 0.7426 | 0.7104 | 0.9514 |
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- | No log | 10.0 | 160 | 0.2292 | 0.6863 | 0.7348 | 0.7097 | 0.9512 |
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- | No log | 11.0 | 176 | 0.2312 | 0.6932 | 0.7452 | 0.7183 | 0.9522 |
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- | No log | 12.0 | 192 | 0.2258 | 0.6966 | 0.7523 | 0.7234 | 0.9535 |
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- | No log | 13.0 | 208 | 0.2337 | 0.7076 | 0.7557 | 0.7309 | 0.9537 |
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- | No log | 14.0 | 224 | 0.2299 | 0.6907 | 0.7549 | 0.7214 | 0.9533 |
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- | No log | 15.0 | 240 | 0.2381 | 0.6980 | 0.7553 | 0.7255 | 0.9524 |
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- | No log | 16.0 | 256 | 0.2411 | 0.6869 | 0.7467 | 0.7156 | 0.9528 |
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  ### Framework versions
 
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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
 
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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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  | 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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