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rubert-base-cased-sentence-kinopoisk
Glepka/rubert-base-cased-sentence-kinopoisk
rubert-base-cased-sentence-kinopoisk is a text classification model from Glepka. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Dec 23, 2025
- Updated
- Dec 23, 2025
- SHA
- be82ba58
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
rubert-base-cased-sentence-kinopoisk
This model is a fine-tuned version of DeepPavlov/rubert-base-cased-sentence on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9717
- Accuracy: 0.7033
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7428 | 1.0 | 891 | 0.6323 | 0.7227 |
| 0.5555 | 2.0 | 1782 | 0.6505 | 0.714 |
| 0.4626 | 3.0 | 2673 | 0.6940 | 0.7133 |
| 0.3513 | 4.0 | 3564 | 0.8145 | 0.7007 |
| 0.2867 | 5.0 | 4455 | 0.9315 | 0.7033 |
| 0.2188 | 6.0 | 5346 | 0.9717 | 0.7033 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Dec 23, 2025
- Updated
- Dec 23, 2025