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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: 0.1777 |
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- Precision: 0.7455 |
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- Recall: 0.7780 |
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- F1: 0.7614 |
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- Accuracy: 0.9616 |
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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 | 0.2251 | 0.5886 | 0.6203 | 0.6040 | 0.9414 | |
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| 0.2833 | 2.0 | 564 | 0.1686 | 0.6566 | 0.6784 | 0.6673 | 0.9505 | |
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| 0.2833 | 3.0 | 846 | 0.1603 | 0.6795 | 0.7303 | 0.7040 | 0.9565 | |
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| 0.0914 | 4.0 | 1128 | 0.1642 | 0.7310 | 0.7386 | 0.7348 | 0.9582 | |
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| 0.0914 | 5.0 | 1410 | 0.1545 | 0.7385 | 0.7676 | 0.7528 | 0.9595 | |
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| 0.0408 | 6.0 | 1692 | 0.1782 | 0.7179 | 0.7552 | 0.7361 | 0.9565 | |
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| 0.0408 | 7.0 | 1974 | 0.1840 | 0.7324 | 0.7552 | 0.7436 | 0.9599 | |
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| 0.0193 | 8.0 | 2256 | 0.1839 | 0.7324 | 0.7552 | 0.7436 | 0.9590 | |
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| 0.0107 | 9.0 | 2538 | 0.1788 | 0.7571 | 0.7697 | 0.7634 | 0.9624 | |
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| 0.0107 | 10.0 | 2820 | 0.1777 | 0.7455 | 0.7780 | 0.7614 | 0.9616 | |
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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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