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Priyanka-Balivada
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Russian-BERT

Text Classification
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bert
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Priyanka-Balivada commited on
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Russian-BERT

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  1. README.md +15 -13
  2. training_args.bin +1 -1
README.md CHANGED
@@ -1,13 +1,13 @@
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  ---
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- base_model: bert-base-uncased
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  library_name: transformers
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  license: apache-2.0
 
 
 
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  metrics:
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  - accuracy
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  - precision
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  - recall
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- tags:
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- - generated_from_trainer
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  model-index:
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  - name: russian-BERT
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  results: []
@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5780
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- - Accuracy: 0.8663
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- - Precision: 0.8662
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- - Recall: 0.8663
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- - Micro-avg-recall: 0.8663
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- - Micro-avg-precision: 0.8663
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  ## Model description
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@@ -50,15 +50,17 @@ The following hyperparameters were used during training:
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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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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:|
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- | 0.4094 | 1.0 | 750 | 0.4025 | 0.8393 | 0.8417 | 0.8393 | 0.8393 | 0.8393 |
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- | 0.3033 | 2.0 | 1500 | 0.4566 | 0.8617 | 0.8618 | 0.8617 | 0.8617 | 0.8617 |
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- | 0.0816 | 3.0 | 2250 | 0.5780 | 0.8663 | 0.8662 | 0.8663 | 0.8663 | 0.8663 |
 
 
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  ### Framework versions
 
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  ---
 
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  library_name: transformers
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  license: apache-2.0
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+ base_model: bert-base-uncased
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+ tags:
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+ - generated_from_trainer
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  metrics:
8
  - accuracy
9
  - precision
10
  - recall
 
 
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  model-index:
12
  - name: russian-BERT
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  results: []
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5708
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+ - Accuracy: 0.8933
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+ - Precision: 0.8933
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+ - Recall: 0.8933
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+ - Micro-avg-recall: 0.8933
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+ - Micro-avg-precision: 0.8933
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  ## Model description
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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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:|
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+ | 0.4304 | 1.0 | 750 | 0.3997 | 0.8397 | 0.8399 | 0.8397 | 0.8397 | 0.8397 |
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+ | 0.3907 | 2.0 | 1500 | 0.3305 | 0.873 | 0.8791 | 0.873 | 0.873 | 0.873 |
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+ | 0.1386 | 3.0 | 2250 | 0.3770 | 0.888 | 0.8898 | 0.888 | 0.888 | 0.888 |
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+ | 0.0631 | 4.0 | 3000 | 0.5419 | 0.8887 | 0.8887 | 0.8887 | 0.8887 | 0.8887 |
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+ | 0.1276 | 5.0 | 3750 | 0.5708 | 0.8933 | 0.8933 | 0.8933 | 0.8933 | 0.8933 |
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  ### Framework versions
training_args.bin CHANGED
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