Pontonkid commited on
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c5b1958
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End of training

Browse files
README.md CHANGED
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  ---
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- base_model: arnabdhar/tinybert-ner
 
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -24,16 +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: 0.4722222222222222
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  - name: Recall
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  type: recall
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- value: 0.40729166666666666
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  - name: F1
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  type: f1
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- value: 0.43736017897091717
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  - name: Accuracy
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  type: accuracy
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- value: 0.9466873494713638
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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
@@ -41,13 +42,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # checkpoint-1000
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- This model is a fine-tuned version of [arnabdhar/tinybert-ner](https://huggingface.co/arnabdhar/tinybert-ner) on the ncbi_disease dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1611
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- - Precision: 0.4722
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- - Recall: 0.4073
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- - F1: 0.4374
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- - Accuracy: 0.9467
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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 | 340 | 0.2055 | 0.2744 | 0.1521 | 0.1957 | 0.9318 |
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- | 0.2656 | 2.0 | 680 | 0.1761 | 0.4051 | 0.3 | 0.3447 | 0.9417 |
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- | 0.1738 | 3.0 | 1020 | 0.1638 | 0.4582 | 0.4 | 0.4271 | 0.9455 |
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- | 0.1738 | 4.0 | 1360 | 0.1611 | 0.4722 | 0.4073 | 0.4374 | 0.9467 |
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  ### Framework versions
 
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  ---
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+ license: mit
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+ base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.8456973293768546
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  - name: Recall
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  type: recall
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+ value: 0.890625
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  - name: F1
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  type: f1
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+ value: 0.8675799086757991
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9850593950279626
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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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  # checkpoint-1000
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+ This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on the ncbi_disease dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0543
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+ - Precision: 0.8457
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+ - Recall: 0.8906
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+ - F1: 0.8676
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+ - Accuracy: 0.9851
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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 | 340 | 0.0596 | 0.7778 | 0.875 | 0.8235 | 0.9795 |
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+ | 0.0787 | 2.0 | 680 | 0.0416 | 0.8246 | 0.8865 | 0.8544 | 0.9851 |
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+ | 0.0202 | 3.0 | 1020 | 0.0494 | 0.8385 | 0.8812 | 0.8593 | 0.9846 |
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+ | 0.0202 | 4.0 | 1360 | 0.0543 | 0.8457 | 0.8906 | 0.8676 | 0.9851 |
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  ### Framework versions
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