Priyanka-Balivada
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Russian-BERT

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 ---
 library_name: transformers
-tags: []
 ---
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 ---
 library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: russian-BERT
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+# russian-BERT
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4908
+- Accuracy: 0.791
+- Precision: 0.7891
+- Recall: 0.791
+- Micro-avg-recall: 0.791
+- Micro-avg-precision: 0.791
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Micro-avg-recall | Micro-avg-precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:----------------:|:-------------------:|
+| 0.4459        | 1.0   | 750  | 0.4908          | 0.791    | 0.7891    | 0.791  | 0.791            | 0.791               |
+### Framework versions
+- Transformers 4.44.2
+- Pytorch 2.4.0
+- Datasets 3.0.0
+- Tokenizers 0.19.1

training_args.bin ADDED Viewed

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