End of training
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README.md
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---
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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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- f1
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- recall
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- accuracy
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- precision
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model-index:
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- name: bert-base-fine-tuned-text-classificarion-ds-dropout
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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-base-fine-tuned-text-classificarion-ds-dropout
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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: 1.0721
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- F1: 0.7307
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- Recall: 0.7499
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- Accuracy: 0.7499
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- Precision: 0.7427
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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: 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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | Precision |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:---------:|
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| No log | 1.0 | 442 | 2.6972 | 0.4056 | 0.4819 | 0.4819 | 0.4782 |
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| 3.5527 | 2.0 | 884 | 1.6292 | 0.5981 | 0.6559 | 0.6559 | 0.6035 |
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| 2.1075 | 3.0 | 1326 | 1.2669 | 0.6801 | 0.7117 | 0.7117 | 0.6923 |
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| 1.2767 | 4.0 | 1768 | 1.0995 | 0.7133 | 0.7437 | 0.7437 | 0.7336 |
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| 0.9148 | 5.0 | 2210 | 1.0721 | 0.7307 | 0.7499 | 0.7499 | 0.7427 |
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### Framework versions
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- Transformers 4.33.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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