DioBot2000
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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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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: BERT-multilingual-finetuned-CEFR_ner-3000news
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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-multilingual-finetuned-CEFR_ner-3000news
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/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: 0.5691
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- Accuracy: 0.4044
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- Precision: 0.4949
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- Recall: 0.6593
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- F1: 0.4688
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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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- num_epochs: 12
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| No log | 1.0 | 132 | 0.5657 | 0.3739 | 0.5044 | 0.5333 | 0.4050 |
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| No log | 2.0 | 264 | 0.5076 | 0.3859 | 0.5011 | 0.5712 | 0.4225 |
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| No log | 3.0 | 396 | 0.4845 | 0.3925 | 0.4690 | 0.6167 | 0.4351 |
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| 0.4009 | 4.0 | 528 | 0.4981 | 0.3985 | 0.4956 | 0.6180 | 0.4514 |
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| 0.4009 | 5.0 | 660 | 0.5136 | 0.3976 | 0.4913 | 0.6348 | 0.4570 |
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| 0.4009 | 6.0 | 792 | 0.5092 | 0.4019 | 0.5004 | 0.6434 | 0.4655 |
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| 0.4009 | 7.0 | 924 | 0.5235 | 0.4012 | 0.4837 | 0.6434 | 0.4555 |
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| 0.1848 | 8.0 | 1056 | 0.5327 | 0.4033 | 0.4948 | 0.6519 | 0.4662 |
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| 0.1848 | 9.0 | 1188 | 0.5640 | 0.4033 | 0.4920 | 0.6536 | 0.4638 |
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| 0.1848 | 10.0 | 1320 | 0.5717 | 0.4031 | 0.4962 | 0.6547 | 0.4677 |
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| 0.1848 | 11.0 | 1452 | 0.5667 | 0.4043 | 0.4910 | 0.6609 | 0.4666 |
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| 0.1096 | 12.0 | 1584 | 0.5691 | 0.4044 | 0.4949 | 0.6593 | 0.4688 |
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### Framework versions
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- Transformers 4.41.1
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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