malduwais commited on
Commit
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End of training

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README.md CHANGED
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  ---
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
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- datasets:
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- - conll2003
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  metrics:
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  - precision
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  - recall
@@ -11,27 +10,7 @@ metrics:
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  - accuracy
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  model-index:
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  - name: distilbert-base-uncased-finetuned-ner
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- results:
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- - task:
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- name: Token Classification
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- type: token-classification
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- dataset:
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- name: conll2003
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- type: conll2003
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- args: conll2003
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- metrics:
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- - name: Precision
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- type: precision
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- value: 0.9244616234124793
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- - name: Recall
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- type: recall
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- value: 0.9364582168027744
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- - name: F1
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- type: f1
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- value: 0.9304212515282871
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- - name: Accuracy
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- type: accuracy
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- value: 0.9833987322668276
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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
@@ -39,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilbert-base-uncased-finetuned-ner
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- This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0623
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- - Precision: 0.9245
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- - Recall: 0.9365
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- - F1: 0.9304
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- - Accuracy: 0.9834
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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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- | 0.2377 | 1.0 | 878 | 0.0711 | 0.9176 | 0.9254 | 0.9215 | 0.9813 |
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- | 0.0514 | 2.0 | 1756 | 0.0637 | 0.9213 | 0.9346 | 0.9279 | 0.9831 |
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- | 0.031 | 3.0 | 2634 | 0.0623 | 0.9245 | 0.9365 | 0.9304 | 0.9834 |
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  ### Framework versions
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- - Transformers 4.12.5
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- - Pytorch 1.10.0+cu111
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- - Datasets 1.16.1
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- - Tokenizers 0.10.3
 
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  ---
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  license: apache-2.0
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+ base_model: distilbert-base-uncased
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - precision
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  - recall
 
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  - accuracy
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  model-index:
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  - name: distilbert-base-uncased-finetuned-ner
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+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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  # distilbert-base-uncased-finetuned-ner
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0601
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+ - Precision: 0.9229
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+ - Recall: 0.9352
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+ - F1: 0.9290
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+ - Accuracy: 0.9831
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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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+ | 0.2538 | 1.0 | 878 | 0.0725 | 0.8985 | 0.9165 | 0.9074 | 0.9792 |
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+ | 0.0514 | 2.0 | 1756 | 0.0593 | 0.9218 | 0.9318 | 0.9267 | 0.9827 |
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+ | 0.0308 | 3.0 | 2634 | 0.0601 | 0.9229 | 0.9352 | 0.9290 | 0.9831 |
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  ### Framework versions
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.0
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+ - Tokenizers 0.15.0
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