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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: multibert1110_lrate5b16 |
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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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# multibert1110_lrate5b16 |
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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: 0.5618 |
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- Precisions: 0.8632 |
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- Recall: 0.8248 |
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- F-measure: 0.8416 |
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- Accuracy: 0.9160 |
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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: 5e-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: 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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| 0.5858 | 1.0 | 236 | 0.3670 | 0.8368 | 0.6841 | 0.7038 | 0.8774 | |
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| 0.302 | 2.0 | 472 | 0.3603 | 0.8064 | 0.7589 | 0.7780 | 0.8931 | |
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| 0.1746 | 3.0 | 708 | 0.3442 | 0.8616 | 0.7693 | 0.7773 | 0.9026 | |
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| 0.118 | 4.0 | 944 | 0.4355 | 0.8683 | 0.7908 | 0.8197 | 0.9039 | |
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| 0.0822 | 5.0 | 1180 | 0.4320 | 0.8775 | 0.8042 | 0.8343 | 0.9094 | |
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| 0.0597 | 6.0 | 1416 | 0.4654 | 0.8722 | 0.8075 | 0.8298 | 0.9089 | |
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| 0.0363 | 7.0 | 1652 | 0.5211 | 0.8768 | 0.7803 | 0.8192 | 0.9054 | |
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| 0.0258 | 8.0 | 1888 | 0.4996 | 0.8631 | 0.8111 | 0.8306 | 0.9133 | |
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| 0.0165 | 9.0 | 2124 | 0.6172 | 0.8984 | 0.7691 | 0.8095 | 0.9073 | |
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| 0.0135 | 10.0 | 2360 | 0.5919 | 0.8912 | 0.7948 | 0.8312 | 0.9130 | |
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| 0.0111 | 11.0 | 2596 | 0.5726 | 0.8704 | 0.8003 | 0.8280 | 0.9143 | |
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| 0.0079 | 12.0 | 2832 | 0.5618 | 0.8632 | 0.8248 | 0.8416 | 0.9160 | |
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| 0.0047 | 13.0 | 3068 | 0.5917 | 0.8674 | 0.7977 | 0.8269 | 0.9149 | |
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| 0.0042 | 14.0 | 3304 | 0.5886 | 0.8685 | 0.8014 | 0.8292 | 0.9161 | |
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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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