End of training
Browse files- README.md +68 -0
- pytorch_model.bin +1 -1
README.md
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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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- 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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---
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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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# 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: 0.0664
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- Precision: 0.9345
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- Recall: 0.9421
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- F1: 0.9383
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- Accuracy: 0.9852
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.0303 | 1.0 | 878 | 0.0579 | 0.9295 | 0.9352 | 0.9324 | 0.9838 |
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| 0.0167 | 2.0 | 1756 | 0.0619 | 0.9333 | 0.9421 | 0.9376 | 0.9849 |
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| 0.0114 | 3.0 | 2634 | 0.0664 | 0.9345 | 0.9421 | 0.9383 | 0.9852 |
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### Framework versions
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- Transformers 4.32.1
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- Pytorch 2.2.0
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- Datasets 2.17.1
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- Tokenizers 0.13.3
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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size 265514530
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version https://git-lfs.github.com/spec/v1
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size 265514530
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