This is a finetuned version of [RuRoBERTa-large](https://huggingface.co/sberbank-ai/ruRoberta-large) for the task of linguistic acceptability classification on the [RuCoLA](https://rucola-benchmark.com/) benchmark.

The hyperparameters used for finetuning are as follows:
* 5 training epochs (with early stopping based on validation MCC)
* Peak learning rate: 1e-5, linear warmup for 10% of total training time
* Weight decay: 1e-4
* Batch size: 32
* Random seed: 5
* Optimizer: [torch.optim.AdamW](https://pytorch.org/docs/stable/generated/torch.optim.AdamW.html)
{"language": "ru", "license": "apache-2.0", "tags": ["transformers"], "thumbnail": "https://github.com/RussianNLP/RuCoLA/blob/main/logo.png", "widget": [{"text": "\u041e\u043d \u0440\u0435\u0448\u0438\u043b \u0442\u0443 \u0438\u043b\u0438 \u0438\u043d\u0443\u044e \u0441\u043b\u043e\u0436\u043d\u0443\u044e \u0437\u0430\u0434\u0430\u0447\u0443."}]}
transformers pytorch roberta text-classification ru license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #ru #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

This is a finetuned version of RuRoBERTa-large for the task of linguistic acceptability classification on the RuCoLA benchmark.

The hyperparameters used for finetuning are as follows:
* 5 training epochs (with early stopping based on validation MCC)
* Peak learning rate: 1e-5, linear warmup for 10% of total training time
* Weight decay: 1e-4
* Batch size: 32
* Random seed: 5
* Optimizer: URL.AdamW
TAGS
#transformers #pytorch #roberta #text-classification #ru #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #roberta #text-classification #ru #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
