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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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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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+ datasets:
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+ - conll2003
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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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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+ config: conll2003
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+ split: validation
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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: 0.921937195931004
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+ - name: Recall
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+ type: recall
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+ value: 0.9327665286944848
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+ - name: F1
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+ type: f1
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+ value: 0.9273202468998499
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9831445501771331
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+ ---
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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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+
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+ # distilbert-base-uncased-finetuned-ner
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+
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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: 0.0629
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+ - Precision: 0.9219
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+ - Recall: 0.9328
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+ - F1: 0.9273
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+ - Accuracy: 0.9831
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2535 | 1.0 | 878 | 0.0703 | 0.8992 | 0.9196 | 0.9093 | 0.9797 |
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+ | 0.0519 | 2.0 | 1756 | 0.0633 | 0.9161 | 0.9271 | 0.9215 | 0.9817 |
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+ | 0.0301 | 3.0 | 2634 | 0.0629 | 0.9219 | 0.9328 | 0.9273 | 0.9831 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 2.4.1
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
config.json ADDED
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+ {
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+ "_name_or_path": "distilbert-base-uncased",
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForTokenClassification"
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+ ],
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+ "transformers_version": "4.45.2",
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+ }
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