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--- |
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license: apache-2.0 |
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base_model: distilbert/distilbert-base-multilingual-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: distilbert-base-multilingual-cased-finetuned-ner-harem |
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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-multilingual-cased-finetuned-ner-harem |
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This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1929 |
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- Precision: 0.7319 |
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- Recall: 0.7531 |
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- F1: 0.7423 |
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- Accuracy: 0.9587 |
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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: 10 |
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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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| No log | 1.0 | 282 | 0.2132 | 0.5566 | 0.6224 | 0.5877 | 0.9403 | |
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| 0.28 | 2.0 | 564 | 0.1715 | 0.6793 | 0.7075 | 0.6931 | 0.9533 | |
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| 0.28 | 3.0 | 846 | 0.1507 | 0.7101 | 0.7469 | 0.7280 | 0.9586 | |
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| 0.0882 | 4.0 | 1128 | 0.1662 | 0.7368 | 0.7261 | 0.7315 | 0.9568 | |
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| 0.0882 | 5.0 | 1410 | 0.1718 | 0.7387 | 0.7448 | 0.7417 | 0.9579 | |
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| 0.0386 | 6.0 | 1692 | 0.1823 | 0.7078 | 0.7490 | 0.7278 | 0.9576 | |
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| 0.0386 | 7.0 | 1974 | 0.1969 | 0.7206 | 0.7490 | 0.7345 | 0.9574 | |
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| 0.0187 | 8.0 | 2256 | 0.1816 | 0.7349 | 0.7593 | 0.7469 | 0.9589 | |
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| 0.0101 | 9.0 | 2538 | 0.1928 | 0.7363 | 0.7531 | 0.7446 | 0.9584 | |
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| 0.0101 | 10.0 | 2820 | 0.1929 | 0.7319 | 0.7531 | 0.7423 | 0.9587 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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