End of training
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- model.safetensors +1 -1
README.md
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---
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base_model: ai-forever/ruBert-large
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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-chn-classifier
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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-chn-classifier
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This model is a fine-tuned version of [ai-forever/ruBert-large](https://huggingface.co/ai-forever/ruBert-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2343
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- Accuracy: 0.9595
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- Precision: 0.9595
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- Recall: 0.9595
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- F1: 0.9595
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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: 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: 3
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- mixed_precision_training: Native AMP
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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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| 0.2249 | 1.0 | 4381 | 0.1770 | 0.9513 | 0.9513 | 0.9513 | 0.9513 |
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| 0.1078 | 2.0 | 8762 | 0.1951 | 0.9571 | 0.9571 | 0.9571 | 0.9571 |
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| 0.0234 | 3.0 | 13143 | 0.2343 | 0.9595 | 0.9595 | 0.9595 | 0.9595 |
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### Framework versions
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- Transformers 4.41.0
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1707694236
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version https://git-lfs.github.com/spec/v1
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size 1707694236
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