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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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model-index:
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- name: 16class_combo_corr_common_tweet_18nov23_v1
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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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# 16class_combo_corr_common_tweet_18nov23_v1
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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: 0.0239
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- Accuracy: 0.9947
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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: 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: 11
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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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| 1.4616 | 1.0 | 609 | 0.5715 | 0.8471 |
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| 0.5821 | 2.0 | 1218 | 0.2933 | 0.9240 |
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| 0.3726 | 3.0 | 1827 | 0.2013 | 0.9471 |
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| 0.2745 | 4.0 | 2436 | 0.1264 | 0.9684 |
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| 0.1724 | 5.0 | 3045 | 0.0916 | 0.9783 |
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| 0.1217 | 6.0 | 3654 | 0.0625 | 0.9862 |
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| 0.0929 | 7.0 | 4263 | 0.0513 | 0.9885 |
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| 0.0839 | 8.0 | 4872 | 0.0356 | 0.9922 |
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| 0.0584 | 9.0 | 5481 | 0.0321 | 0.9926 |
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| 0.0383 | 10.0 | 6090 | 0.0253 | 0.9948 |
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| 0.0398 | 11.0 | 6699 | 0.0239 | 0.9947 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.1+cu121
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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