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---
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library_name: transformers
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license: apache-2.0
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base_model: 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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- accuracy
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model-index:
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- name: results_fine_tune_gpt40_original_careful
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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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# results_fine_tune_gpt40_original_careful
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/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: 0.0019
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- Accuracy: 0.9993
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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: 1e-05
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- train_batch_size: 8
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 0.0049 | 0.8881 | 500 | 0.0082 | 0.9987 |
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| 0.0056 | 1.7762 | 1000 | 0.0226 | 0.9973 |
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| 0.0062 | 2.6643 | 1500 | 0.0003 | 1.0 |
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| 0.0031 | 3.5524 | 2000 | 0.0009 | 0.9993 |
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| 0.0006 | 4.4405 | 2500 | 0.0019 | 0.9993 |
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### Framework versions
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- Transformers 4.47.1
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- Pytorch 2.5.1+cu124
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- Datasets 2.17.0
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- Tokenizers 0.21.0
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