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End of training

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README.md ADDED
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+ ---
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+ base_model: distilbert-base-cased
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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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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: ner-distilbert
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+ results: []
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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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+ # ner-distilbert
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+
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+ This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0003
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+ - Precision: 0.9988
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+ - Recall: 0.9980
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+ - F1: 0.9984
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+ - Accuracy: 0.9998
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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: 4
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+ - eval_batch_size: 4
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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: 1
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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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+ | 0.0002 | 0.16 | 250 | 0.0011 | 0.9961 | 0.9980 | 0.9971 | 0.9996 |
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+ | 0.0001 | 0.31 | 500 | 0.0008 | 0.9977 | 0.9977 | 0.9977 | 0.9997 |
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+ | 0.0004 | 0.47 | 750 | 0.0005 | 0.9992 | 0.9977 | 0.9984 | 0.9998 |
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+ | 0.0002 | 0.63 | 1000 | 0.0005 | 0.9984 | 0.9977 | 0.9980 | 0.9997 |
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+ | 0.0002 | 0.79 | 1250 | 0.0003 | 0.9988 | 0.9980 | 0.9984 | 0.9998 |
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+ | 0.0 | 0.94 | 1500 | 0.0003 | 0.9988 | 0.9980 | 0.9984 | 0.9998 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.1.0
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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