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bert-base-spanish-wwm-uncased-finetuned-ner

Token Classification
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  1. README.md +20 -20
  2. runs/Dec05_17-14-07_ed2b090b53d4/events.out.tfevents.1733419444.ed2b090b53d4.234.2 +2 -2
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: bert-base-spanish-wwm-uncased-finetuned-ner1
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  results:
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  - task:
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  name: Token Classification
@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9483257314495495
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  - name: Recall
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  type: recall
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- value: 0.9656754460492778
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  - name: F1
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  type: f1
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- value: 0.9569219543681419
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  - name: Accuracy
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  type: accuracy
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- value: 0.9766181574620958
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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
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the biobert_json dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1423
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- - Precision: 0.9483
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- - Recall: 0.9657
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- - F1: 0.9569
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- - Accuracy: 0.9766
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  ## Model description
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@@ -79,16 +79,16 @@ 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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- | 0.0179 | 1.0 | 612 | 0.1292 | 0.9547 | 0.9629 | 0.9588 | 0.9779 |
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- | 0.0133 | 2.0 | 1224 | 0.1574 | 0.9463 | 0.9684 | 0.9572 | 0.9766 |
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- | 0.0146 | 3.0 | 1836 | 0.1179 | 0.9500 | 0.9622 | 0.9561 | 0.9769 |
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- | 0.0238 | 4.0 | 2448 | 0.1388 | 0.9441 | 0.9677 | 0.9557 | 0.9759 |
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- | 0.0152 | 5.0 | 3060 | 0.1442 | 0.9430 | 0.9634 | 0.9531 | 0.9754 |
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- | 0.0155 | 6.0 | 3672 | 0.1401 | 0.9480 | 0.9641 | 0.9560 | 0.9760 |
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- | 0.0126 | 7.0 | 4284 | 0.1411 | 0.9468 | 0.9676 | 0.9571 | 0.9769 |
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- | 0.0131 | 8.0 | 4896 | 0.1427 | 0.9484 | 0.9657 | 0.9570 | 0.9767 |
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- | 0.0117 | 9.0 | 5508 | 0.1391 | 0.9485 | 0.9651 | 0.9567 | 0.9767 |
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- | 0.0116 | 10.0 | 6120 | 0.1423 | 0.9483 | 0.9657 | 0.9569 | 0.9766 |
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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: bert-base-spanish-wwm-uncased-finetuned-ner
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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: 0.9499079600602444
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  - name: Recall
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  type: recall
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+ value: 0.9645426224865478
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  - name: F1
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  type: f1
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+ value: 0.9571693552920016
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  - name: Accuracy
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  type: accuracy
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+ value: 0.977242282165256
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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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  This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased) on the biobert_json dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1255
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+ - Precision: 0.9499
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+ - Recall: 0.9645
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+ - F1: 0.9572
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+ - Accuracy: 0.9772
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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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+ | 0.0412 | 1.0 | 612 | 0.1343 | 0.9401 | 0.9624 | 0.9512 | 0.9734 |
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+ | 0.0632 | 2.0 | 1224 | 0.1082 | 0.9360 | 0.9654 | 0.9505 | 0.9746 |
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+ | 0.0568 | 3.0 | 1836 | 0.1070 | 0.9469 | 0.9659 | 0.9563 | 0.9765 |
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+ | 0.0486 | 4.0 | 2448 | 0.1104 | 0.9477 | 0.9669 | 0.9572 | 0.9771 |
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+ | 0.0334 | 5.0 | 3060 | 0.1158 | 0.9425 | 0.9643 | 0.9533 | 0.9756 |
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+ | 0.0311 | 6.0 | 3672 | 0.1238 | 0.9449 | 0.9644 | 0.9546 | 0.9753 |
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+ | 0.0249 | 7.0 | 4284 | 0.1178 | 0.9473 | 0.9652 | 0.9561 | 0.9767 |
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+ | 0.0245 | 8.0 | 4896 | 0.1244 | 0.9483 | 0.9656 | 0.9569 | 0.9772 |
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+ | 0.0185 | 9.0 | 5508 | 0.1227 | 0.9492 | 0.9643 | 0.9567 | 0.9771 |
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+ | 0.0165 | 10.0 | 6120 | 0.1255 | 0.9499 | 0.9645 | 0.9572 | 0.9772 |
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  ### Framework versions
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