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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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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: tiny-vanilla-target-conll2003
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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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# tiny-vanilla-target-conll2003
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This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1431
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- Precision: 0.7507
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- Recall: 0.8177
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- F1: 0.7828
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- Accuracy: 0.9581
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: constant
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- training_steps: 5000
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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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| 0.7673 | 1.14 | 500 | 0.4291 | 0.4793 | 0.5160 | 0.4970 | 0.8920 |
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| 0.3746 | 2.28 | 1000 | 0.2869 | 0.5976 | 0.6572 | 0.6260 | 0.9256 |
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| 0.2869 | 3.42 | 1500 | 0.2292 | 0.6411 | 0.7184 | 0.6776 | 0.9370 |
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| 0.236 | 4.56 | 2000 | 0.1988 | 0.6805 | 0.7516 | 0.7143 | 0.9438 |
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| 0.2026 | 5.69 | 2500 | 0.1772 | 0.7047 | 0.7718 | 0.7367 | 0.9482 |
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| 0.1798 | 6.83 | 3000 | 0.1649 | 0.7179 | 0.7864 | 0.7506 | 0.9514 |
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| 0.158 | 7.97 | 3500 | 0.1559 | 0.7256 | 0.7987 | 0.7604 | 0.9543 |
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| 0.1415 | 9.11 | 4000 | 0.1500 | 0.7379 | 0.8034 | 0.7693 | 0.9563 |
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| 0.127 | 10.25 | 4500 | 0.1462 | 0.7532 | 0.8134 | 0.7821 | 0.9573 |
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| 0.1173 | 11.39 | 5000 | 0.1431 | 0.7507 | 0.8177 | 0.7828 | 0.9581 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.0+cu116
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- Datasets 2.8.1.dev0
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- Tokenizers 0.13.2
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