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---
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license: apache-2.0
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base_model: distilbert/distilbert-base-multilingual-cased
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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: NEW_trained_english
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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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# NEW_trained_english
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This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-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: 0.1146
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- Precision: 0.7363
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- Recall: 0.7212
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- F1: 0.7287
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- Accuracy: 0.9767
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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: 3e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 16
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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: 4
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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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| 0.1114 | 1.0 | 784 | 0.0881 | 0.7161 | 0.7397 | 0.7277 | 0.9756 |
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| 0.0308 | 2.0 | 1568 | 0.1023 | 0.7348 | 0.6738 | 0.7030 | 0.9749 |
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| 0.0155 | 3.0 | 2352 | 0.1055 | 0.7588 | 0.7109 | 0.7340 | 0.9775 |
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| 0.0062 | 4.0 | 3136 | 0.1146 | 0.7363 | 0.7212 | 0.7287 | 0.9767 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.1.2+cu118
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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