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Training complete
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README.md
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---
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license: apache-2.0
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base_model: 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: NLP-HIBA2_DisTEMIST_fine_tuned_biobert-pretrained-model
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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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# NLP-HIBA2_DisTEMIST_fine_tuned_biobert-pretrained-model
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/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: 0.1602
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- Precision: 0.5278
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- Recall: 0.4527
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- F1: 0.4874
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- Accuracy: 0.9479
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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: 8
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- eval_batch_size: 8
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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: 5
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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 | 71 | 0.1798 | 0.3590 | 0.2669 | 0.3062 | 0.9316 |
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| No log | 2.0 | 142 | 0.1570 | 0.4772 | 0.3407 | 0.3976 | 0.9433 |
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| No log | 3.0 | 213 | 0.1506 | 0.4967 | 0.4245 | 0.4578 | 0.9456 |
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| No log | 4.0 | 284 | 0.1601 | 0.5402 | 0.4297 | 0.4787 | 0.9485 |
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| No log | 5.0 | 355 | 0.1602 | 0.5278 | 0.4527 | 0.4874 | 0.9479 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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