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--- |
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language: |
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- mn |
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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: mongolian-distilbert-base-multilingual-cased-demo |
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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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# mongolian-distilbert-base-multilingual-cased-demo |
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/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: 0.1370 |
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- Precision: 0.8794 |
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- Recall: 0.9055 |
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- F1: 0.8923 |
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- Accuracy: 0.9724 |
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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: 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: 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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| 0.2163 | 1.0 | 477 | 0.1387 | 0.7933 | 0.8434 | 0.8176 | 0.9560 | |
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| 0.1049 | 2.0 | 954 | 0.0989 | 0.8491 | 0.8840 | 0.8662 | 0.9688 | |
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| 0.0705 | 3.0 | 1431 | 0.0948 | 0.8598 | 0.8955 | 0.8773 | 0.9715 | |
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| 0.0476 | 4.0 | 1908 | 0.1065 | 0.8577 | 0.8969 | 0.8768 | 0.9701 | |
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| 0.0336 | 5.0 | 2385 | 0.1142 | 0.8703 | 0.8995 | 0.8847 | 0.9718 | |
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| 0.0252 | 6.0 | 2862 | 0.1225 | 0.8758 | 0.9023 | 0.8888 | 0.9716 | |
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| 0.018 | 7.0 | 3339 | 0.1256 | 0.8738 | 0.9022 | 0.8877 | 0.9716 | |
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| 0.0135 | 8.0 | 3816 | 0.1322 | 0.8807 | 0.9081 | 0.8942 | 0.9731 | |
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| 0.0103 | 9.0 | 4293 | 0.1367 | 0.8767 | 0.9043 | 0.8903 | 0.9720 | |
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| 0.0087 | 10.0 | 4770 | 0.1370 | 0.8794 | 0.9055 | 0.8923 | 0.9724 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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