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bert-finetuned-ner

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  ---
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  license: apache-2.0
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- base_model: bert-base-cased
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  tags:
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  - generated_from_trainer
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  datasets:
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  dataset:
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  name: tweetner7
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  type: tweetner7
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- config: tweetner7
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- split: validation_2021
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  args: tweetner7
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.7025612778848802
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  - name: Recall
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  type: recall
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- value: 0.6474619289340101
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  - name: F1
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  type: f1
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- value: 0.6738872011623299
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  - name: Accuracy
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  type: accuracy
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- value: 0.8775995608952857
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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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the tweetner7 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4089
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- - Precision: 0.7026
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- - Recall: 0.6475
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- - F1: 0.6739
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- - Accuracy: 0.8776
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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 | 312 | 0.4428 | 0.7259 | 0.5860 | 0.6485 | 0.8705 |
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- | 0.5414 | 2.0 | 624 | 0.4090 | 0.7146 | 0.6297 | 0.6695 | 0.8775 |
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- | 0.5414 | 3.0 | 936 | 0.4089 | 0.7026 | 0.6475 | 0.6739 | 0.8776 |
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  ### Framework versions
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- - Transformers 4.31.0
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- - Pytorch 2.0.1+cu118
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- - Datasets 2.13.1
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- - Tokenizers 0.13.3
 
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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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  dataset:
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  name: tweetner7
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  type: tweetner7
 
 
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  args: tweetner7
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  metrics:
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  - name: Precision
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  type: precision
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+ value: 0.6747522170057382
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  - name: Recall
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  type: recall
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+ value: 0.6565989847715736
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  - name: F1
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  type: f1
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+ value: 0.6655518394648829
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8729035799231567
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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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the tweetner7 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4113
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+ - Precision: 0.6748
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+ - Recall: 0.6566
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+ - F1: 0.6656
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+ - Accuracy: 0.8729
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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 | 312 | 0.4366 | 0.7320 | 0.5947 | 0.6562 | 0.8730 |
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+ | 0.5402 | 2.0 | 624 | 0.4120 | 0.7271 | 0.6127 | 0.6650 | 0.8763 |
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+ | 0.5402 | 3.0 | 936 | 0.4113 | 0.6748 | 0.6566 | 0.6656 | 0.8729 |
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  ### Framework versions
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+ - Transformers 4.20.1
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+ - Pytorch 1.12.1
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+ - Datasets 2.10.1
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+ - Tokenizers 0.12.1