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--- |
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license: cc-by-4.0 |
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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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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: small-e-czech-finetuned-ner-wikiann |
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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: wikiann |
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type: wikiann |
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args: cs |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8713322894683097 |
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- name: Recall |
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type: recall |
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value: 0.8970423324922905 |
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- name: F1 |
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type: f1 |
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value: 0.8840004144075699 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9557089381093997 |
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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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# small-e-czech-finetuned-ner-wikiann |
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This model is a fine-tuned version of [Seznam/small-e-czech](https://huggingface.co/Seznam/small-e-czech) on the wikiann dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2547 |
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- Precision: 0.8713 |
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- Recall: 0.8970 |
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- F1: 0.8840 |
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- Accuracy: 0.9557 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 20 |
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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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| 0.2924 | 1.0 | 2500 | 0.2449 | 0.7686 | 0.8088 | 0.7882 | 0.9320 | |
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| 0.2042 | 2.0 | 5000 | 0.2137 | 0.8050 | 0.8398 | 0.8220 | 0.9400 | |
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| 0.1699 | 3.0 | 7500 | 0.1912 | 0.8236 | 0.8593 | 0.8411 | 0.9466 | |
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| 0.1419 | 4.0 | 10000 | 0.1931 | 0.8349 | 0.8671 | 0.8507 | 0.9488 | |
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| 0.1316 | 5.0 | 12500 | 0.1892 | 0.8470 | 0.8776 | 0.8620 | 0.9519 | |
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| 0.1042 | 6.0 | 15000 | 0.2058 | 0.8433 | 0.8811 | 0.8618 | 0.9508 | |
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| 0.0884 | 7.0 | 17500 | 0.2020 | 0.8602 | 0.8849 | 0.8724 | 0.9531 | |
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| 0.0902 | 8.0 | 20000 | 0.2118 | 0.8551 | 0.8837 | 0.8692 | 0.9528 | |
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| 0.0669 | 9.0 | 22500 | 0.2171 | 0.8634 | 0.8906 | 0.8768 | 0.9550 | |
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| 0.0529 | 10.0 | 25000 | 0.2228 | 0.8638 | 0.8912 | 0.8773 | 0.9545 | |
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| 0.0613 | 11.0 | 27500 | 0.2293 | 0.8626 | 0.8898 | 0.8760 | 0.9544 | |
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| 0.0549 | 12.0 | 30000 | 0.2276 | 0.8694 | 0.8958 | 0.8824 | 0.9554 | |
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| 0.0516 | 13.0 | 32500 | 0.2384 | 0.8717 | 0.8940 | 0.8827 | 0.9552 | |
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| 0.0412 | 14.0 | 35000 | 0.2443 | 0.8701 | 0.8931 | 0.8815 | 0.9554 | |
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| 0.0345 | 15.0 | 37500 | 0.2464 | 0.8723 | 0.8958 | 0.8839 | 0.9557 | |
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| 0.0412 | 16.0 | 40000 | 0.2477 | 0.8705 | 0.8948 | 0.8825 | 0.9552 | |
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| 0.0363 | 17.0 | 42500 | 0.2525 | 0.8742 | 0.8973 | 0.8856 | 0.9559 | |
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| 0.0341 | 18.0 | 45000 | 0.2529 | 0.8727 | 0.8962 | 0.8843 | 0.9561 | |
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| 0.0194 | 19.0 | 47500 | 0.2533 | 0.8699 | 0.8966 | 0.8830 | 0.9557 | |
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| 0.0247 | 20.0 | 50000 | 0.2547 | 0.8713 | 0.8970 | 0.8840 | 0.9557 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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