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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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- 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: multibertfinetuned2408 |
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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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# multibertfinetuned2408 |
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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: 0.3350 |
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- Precision: 0.7395 |
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- Recall: 0.7408 |
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- F1: 0.7401 |
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- Accuracy: 0.9041 |
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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: 8 |
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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 | 236 | 0.3641 | 0.6769 | 0.6472 | 0.6617 | 0.8806 | |
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| No log | 2.0 | 472 | 0.3733 | 0.7173 | 0.6741 | 0.6950 | 0.8906 | |
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| 0.429 | 3.0 | 708 | 0.3350 | 0.7395 | 0.7408 | 0.7401 | 0.9041 | |
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| 0.429 | 4.0 | 944 | 0.4290 | 0.7572 | 0.7279 | 0.7422 | 0.9030 | |
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| 0.1313 | 5.0 | 1180 | 0.4485 | 0.7432 | 0.7332 | 0.7381 | 0.9007 | |
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| 0.1313 | 6.0 | 1416 | 0.4799 | 0.7785 | 0.7425 | 0.7601 | 0.9100 | |
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| 0.0504 | 7.0 | 1652 | 0.5249 | 0.7875 | 0.7461 | 0.7662 | 0.9103 | |
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| 0.0504 | 8.0 | 1888 | 0.5146 | 0.7863 | 0.7513 | 0.7684 | 0.9120 | |
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### Framework versions |
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- Transformers 4.32.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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