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--- |
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license: apache-2.0 |
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base_model: bert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wikiann |
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model-index: |
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- name: fine_tuned_BERT_cs_wikann |
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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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# fine_tuned_BERT_cs_wikann |
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the wikiann dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1428 |
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- Overall Precision: 0.9090 |
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- Overall Recall: 0.9274 |
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- Overall F1: 0.9181 |
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- Overall Accuracy: 0.9673 |
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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: 3.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
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| 0.3011 | 0.4 | 500 | 0.1781 | 0.8588 | 0.8721 | 0.8654 | 0.9501 | |
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| 0.1717 | 0.8 | 1000 | 0.1524 | 0.8733 | 0.9033 | 0.8880 | 0.9565 | |
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| 0.1307 | 1.2 | 1500 | 0.1443 | 0.9058 | 0.9051 | 0.9054 | 0.9639 | |
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| 0.0968 | 1.6 | 2000 | 0.1392 | 0.9075 | 0.9107 | 0.9091 | 0.9651 | |
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| 0.0974 | 2.0 | 2500 | 0.1352 | 0.9030 | 0.9201 | 0.9115 | 0.9647 | |
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| 0.0603 | 2.4 | 3000 | 0.1410 | 0.9091 | 0.9217 | 0.9154 | 0.9667 | |
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| 0.054 | 2.8 | 3500 | 0.1428 | 0.9090 | 0.9274 | 0.9181 | 0.9673 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.15.0 |
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