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---
library_name: transformers
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ruBertTiny_attr_name_addv3
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. -->
# ruBertTiny_attr_name_addv3
This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2154
- Accuracy: 0.9188
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:------:|:---------------:|:--------:|
| 0.5515 | 0.2739 | 10000 | 0.4502 | 0.7949 |
| 0.49 | 0.5478 | 20000 | 0.3874 | 0.8205 |
| 0.4632 | 0.8217 | 30000 | 0.3556 | 0.8376 |
| 0.4367 | 1.0956 | 40000 | 0.3381 | 0.8419 |
| 0.4122 | 1.3695 | 50000 | 0.3138 | 0.8590 |
| 0.3989 | 1.6434 | 60000 | 0.2787 | 0.8932 |
| 0.389 | 1.9173 | 70000 | 0.2741 | 0.8846 |
| 0.3669 | 2.1912 | 80000 | 0.2523 | 0.9017 |
| 0.3566 | 2.4651 | 90000 | 0.2459 | 0.8932 |
| 0.3502 | 2.7391 | 100000 | 0.2343 | 0.9017 |
| 0.3458 | 3.0130 | 110000 | 0.2248 | 0.9145 |
| 0.3281 | 3.2869 | 120000 | 0.2203 | 0.9145 |
| 0.3255 | 3.5608 | 130000 | 0.2162 | 0.9145 |
| 0.3234 | 3.8347 | 140000 | 0.2176 | 0.9274 |
| 0.3174 | 4.1086 | 150000 | 0.2147 | 0.9188 |
| 0.3126 | 4.3825 | 160000 | 0.2138 | 0.9145 |
| 0.3127 | 4.6564 | 170000 | 0.2155 | 0.9188 |
| 0.3126 | 4.9303 | 180000 | 0.2154 | 0.9188 |
### Framework versions
- Transformers 4.44.1
- Pytorch 2.0.1+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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