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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_all9k_promptcorr_tweet_300other_23nov23_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_all9k_promptcorr_tweet_300other_23nov23_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: 0.0267
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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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| 1.5225 | 1.0 | 721 | 0.6075 | 0.8344 |
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| 0.7164 | 2.0 | 1442 | 0.3430 | 0.9051 |
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| 0.3828 | 3.0 | 2163 | 0.2532 | 0.9271 |
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| 0.318 | 4.0 | 2884 | 0.1631 | 0.9572 |
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| 0.2131 | 5.0 | 3605 | 0.1231 | 0.9676 |
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| 0.1728 | 6.0 | 4326 | 0.0822 | 0.9807 |
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| 0.1344 | 7.0 | 5047 | 0.0657 | 0.9849 |
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| 0.0902 | 8.0 | 5768 | 0.0471 | 0.9887 |
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| 0.0842 | 9.0 | 6489 | 0.0383 | 0.9912 |
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| 0.0609 | 10.0 | 7210 | 0.0281 | 0.9941 |
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| 0.0512 | 11.0 | 7931 | 0.0267 | 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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