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--- |
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license: apache-2.0 |
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base_model: google-bert/bert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: fine_tuned_bert |
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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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# fine_tuned_bert |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1299 |
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- F1: 0.8444 |
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- F5: 0.8373 |
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- Precision: 0.8636 |
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- Recall: 0.8261 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 33 | 0.3776 | 0.0 | 0.0 | 0.0 | 0.0 | |
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| No log | 2.0 | 66 | 0.2996 | 0.4 | 0.3359 | 0.8 | 0.2667 | |
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| No log | 3.0 | 99 | 0.2137 | 0.7273 | 0.7534 | 0.6667 | 0.8 | |
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| No log | 4.0 | 132 | 0.2161 | 0.6429 | 0.6258 | 0.6923 | 0.6 | |
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| No log | 5.0 | 165 | 0.2367 | 0.6154 | 0.5812 | 0.7273 | 0.5333 | |
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| No log | 6.0 | 198 | 0.1997 | 0.7451 | 0.6980 | 0.9048 | 0.6333 | |
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| No log | 7.0 | 231 | 0.2023 | 0.8000 | 0.8 | 0.8 | 0.8 | |
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| No log | 8.0 | 264 | 0.2011 | 0.8070 | 0.7911 | 0.8519 | 0.7667 | |
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| No log | 9.0 | 297 | 0.2196 | 0.7857 | 0.7648 | 0.8462 | 0.7333 | |
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| No log | 10.0 | 330 | 0.2509 | 0.7667 | 0.7667 | 0.7667 | 0.7667 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.3.0a0+ebedce2 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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