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--- |
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license: apache-2.0 |
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base_model: bert-base-multilingual-uncased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- recall |
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- accuracy |
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model-index: |
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- name: multibert_1210seed85 |
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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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# multibert_1210seed85 |
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This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4043 |
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- Precisions: 0.8689 |
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- Recall: 0.8339 |
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- F-measure: 0.8498 |
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- Accuracy: 0.9067 |
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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: 7.5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 85 |
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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: 14 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:| |
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| 0.5968 | 1.0 | 236 | 0.4307 | 0.8843 | 0.6749 | 0.7165 | 0.8690 | |
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| 0.3238 | 2.0 | 472 | 0.3849 | 0.8827 | 0.7215 | 0.7489 | 0.8916 | |
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| 0.2021 | 3.0 | 708 | 0.4067 | 0.8540 | 0.7640 | 0.7969 | 0.8983 | |
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| 0.1335 | 4.0 | 944 | 0.3857 | 0.8227 | 0.8002 | 0.8071 | 0.8983 | |
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| 0.0886 | 5.0 | 1180 | 0.4043 | 0.8689 | 0.8339 | 0.8498 | 0.9067 | |
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| 0.0654 | 6.0 | 1416 | 0.4734 | 0.8847 | 0.8016 | 0.8359 | 0.9089 | |
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| 0.0451 | 7.0 | 1652 | 0.5312 | 0.8215 | 0.7826 | 0.7996 | 0.8980 | |
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| 0.031 | 8.0 | 1888 | 0.5520 | 0.8730 | 0.7873 | 0.8222 | 0.9074 | |
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| 0.0248 | 9.0 | 2124 | 0.4954 | 0.8896 | 0.8145 | 0.8454 | 0.9149 | |
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| 0.0149 | 10.0 | 2360 | 0.5595 | 0.8717 | 0.8101 | 0.8354 | 0.9104 | |
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| 0.0086 | 11.0 | 2596 | 0.5703 | 0.8814 | 0.8051 | 0.8348 | 0.9112 | |
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| 0.0061 | 12.0 | 2832 | 0.5855 | 0.8655 | 0.8138 | 0.8356 | 0.9103 | |
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| 0.006 | 13.0 | 3068 | 0.6068 | 0.8578 | 0.8137 | 0.8329 | 0.9105 | |
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| 0.0039 | 14.0 | 3304 | 0.6147 | 0.8656 | 0.8129 | 0.8356 | 0.9112 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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