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--- |
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base_model: google-bert/bert-base-multilingual-cased |
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library_name: transformers |
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license: apache-2.0 |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: bert-f1-durga-muhammad |
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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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# bert-f1-durga-muhammad |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-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: 0.0079 |
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- Accuracy: 0.999 |
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- Precision: 0.999 |
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- Recall: 0.999 |
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- F1: 0.999 |
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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: 4 |
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- eval_batch_size: 8 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:-----:| |
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| 0.1978 | 0.24 | 60 | 0.1764 | 0.968 | 0.968 | 0.968 | 0.968 | |
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| 0.1657 | 0.48 | 120 | 0.0619 | 0.981 | 0.981 | 0.981 | 0.981 | |
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| 0.1155 | 0.72 | 180 | 0.0475 | 0.989 | 0.989 | 0.989 | 0.989 | |
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| 0.0675 | 0.96 | 240 | 0.0143 | 0.997 | 0.997 | 0.997 | 0.997 | |
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| 0.0009 | 1.2 | 300 | 0.0148 | 0.997 | 0.997 | 0.997 | 0.997 | |
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| 0.0006 | 1.44 | 360 | 0.0151 | 0.997 | 0.997 | 0.997 | 0.997 | |
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| 0.0267 | 1.6800 | 420 | 0.0083 | 0.999 | 0.999 | 0.999 | 0.999 | |
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| 0.0335 | 1.92 | 480 | 0.0080 | 0.999 | 0.999 | 0.999 | 0.999 | |
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| 0.0315 | 2.16 | 540 | 0.0073 | 0.999 | 0.999 | 0.999 | 0.999 | |
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| 0.0056 | 2.4 | 600 | 0.0076 | 0.999 | 0.999 | 0.999 | 0.999 | |
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| 0.0004 | 2.64 | 660 | 0.0078 | 0.999 | 0.999 | 0.999 | 0.999 | |
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| 0.0004 | 2.88 | 720 | 0.0079 | 0.999 | 0.999 | 0.999 | 0.999 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.5.0+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.19.1 |
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