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roberta
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  1. README.md +19 -14
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  ---
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- base_model: ai-forever/ruRoberta-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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  model-index:
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  - name: logs
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  results: []
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  # logs
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- This model is a fine-tuned version of [ai-forever/ruRoberta-large](https://huggingface.co/ai-forever/ruRoberta-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.8738
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- - Accuracy: 0.2116
 
 
 
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  ## Model description
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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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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 95 | 4.0504 | 0.0 |
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- | No log | 2.0 | 190 | 3.5087 | 0.0529 |
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- | No log | 3.0 | 285 | 3.1335 | 0.1958 |
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- | No log | 4.0 | 380 | 2.8738 | 0.2116 |
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  ### Framework versions
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- - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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- - Tokenizers 0.15.2
 
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  ---
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+ base_model: microsoft/codebert-base
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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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  model-index:
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  - name: logs
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  results: []
 
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  # logs
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+ This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0405
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+ - Accuracy: 0.9950
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+ - Precision: 0.9950
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+ - Recall: 0.9950
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+ - F1 Score: 0.9950
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  ## Model description
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
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+ | 0.1436 | 1.0 | 907 | 0.0851 | 0.9829 | 0.9829 | 0.9829 | 0.9829 |
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+ | 0.0737 | 2.0 | 1814 | 0.0548 | 0.9915 | 0.9915 | 0.9915 | 0.9915 |
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+ | 0.0216 | 3.0 | 2721 | 0.0469 | 0.9917 | 0.9918 | 0.9917 | 0.9917 |
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+ | 0.0143 | 4.0 | 3628 | 0.0405 | 0.9950 | 0.9950 | 0.9950 | 0.9950 |
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  ### Framework versions
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+ - Transformers 4.40.0
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.19.0
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+ - Tokenizers 0.19.1