Upload model, tokenizer, and documentation

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+rsg.jpg filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+library_name: transformers
+license: apache-2.0
+datasets:
+- deepvk/cultura_ru_edu
+- HuggingFaceFW/fineweb-2
+- HuggingFaceFW/fineweb
+language:
+- ru
+- en
+pipeline_tag: fill-mask
+---
+
+# RuModernBERT-base
+
+The Russian version of the modernized bidirectional encoder-only Transformer model, [ModernBERT](https://arxiv.org/abs/2412.13663).
+RuModernBERT was pre-trained on approximately 2 trillion tokens of Russian, English, and code data with a context length of up to 8,192 tokens, using data from the internet, books, scientific sources, and social media.
+
+|                                                                               | Model Size | Hidden Dim | Num Layers | Vocab Size | Context Length |    Task   |
+|------------------------------------------------------------------------------:|:----------:|:----------:|:----------:|:----------:|:--------------:|:---------:|
+| [deepvk/RuModernBERT-small](https://huggingface.co/deepvk/RuModernBERT-small) |     35M    |     384    |     12     |    50368   |      8192      | Masked LM |
+|                                               deepvk/RuModernBERT-base [this] |    150M    |     768    |     22     |    50368   |      8192      | Masked LM |
+
+
+## Usage
+
+Don't forget to update `transformers` and install `flash-attn` if your GPU supports it.
+
+```python
+from transformers import AutoTokenizer, AutoModelForMaskedLM
+
+# Prepare model
+model_id = "deepvk/RuModernBERT-base"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForMaskedLM.from_pretrained(model_id, attn_implementation="flash_attention_2")
+model = model.eval()
+
+# Prepare input
+text = "Лимончелло это настойка из [MASK]."
+inputs = tokenizer(text, return_tensors="pt")
+masked_index = inputs["input_ids"][0].tolist().index(tokenizer.mask_token_id)
+
+# Make prediction
+outputs = model(**inputs)
+
+# Show prediction
+predicted_token_id = outputs.logits[0, masked_index].argmax(axis=-1)
+predicted_token = tokenizer.decode(predicted_token_id)
+print("Predicted token:", predicted_token)
+# Predicted token:  лимона
+```
+
+## Training Details
+
+This is the base version with 150 million parameters and the same configuration as in [`ModernBERT-base`](https://huggingface.co/answerdotai/ModernBERT-base).
+The crucial difference lies in the data we used to pre-train this model.
+
+### Tokenizer
+
+We trained a new tokenizer following the original configuration.
+We maintained the size of the vocabulary and added the same special tokens.
+The tokenizer was trained on a mixture of Russian and English from FineWeb.
+
+### Dataset
+
+Pre-training includes three main stages: massive pre-training, context extension, and cooldown.
+Unlike the original model, we did not use the same data for all stages.
+For the second and third stages, we used cleaner data sources.
+
+|           Data Source | Stage 1  | Stage 2 | Stage 3  |
+|----------------------:|:--------:|:-------:|:--------:|
+|       FineWeb (En+Ru) |    ✅    |    ❌    |    ❌    |
+|  CulturaX-Ru-Edu (Ru) |    ❌    |    ✅    |    ❌    |
+|          Wiki (En+Ru) |    ✅    |    ✅    |    ✅    |
+|            ArXiv (En) |    ✅    |    ✅    |    ✅    |
+|          Book (En+Ru) |    ✅    |    ✅    |    ✅    |
+|                  Code |    ✅    |    ✅    |    ✅    |
+| StackExchange (En+Ru) |    ✅    |    ✅    |    ✅    |
+|           Social (Ru) |    ✅    |    ✅    |    ✅    |
+|      **Total Tokens** |   1.7T   |   250B  |    50B   |
+
+
+### Context length
+
+In the first stage, the model was trained with a context length of `1,024`.
+In the second and third stages, it was extended to `8,192`.
+
+## Evaluation
+
+To evaluate the model, we measure quality on the [`encodechka`](https://github.com/avidale/encodechka) and [`Russian Super Glue (RSG)`](https://russiansuperglue.com/) benchmarks.
+For RSG, we perform a grid search for optimal hyperparameters and report metrics from the **dev** split.
+
+For a fair comparison, we compare the RuModernBERT model only with raw encoders that were not trained on retrieval or sentence embedding tasks.
+
+### Russian Super Glue
+
+<img src="./rsg.jpg">
+
+| Model                                                                          | RCB       |  PARus | MuSeRC  | TERRa | RUSSE   | RWSD    | DaNetQA | Score     |
+|-------------------------------------------------------------------------------:|:---------:|:------:|:-------:|:-----:|:-------:|:-------:|:-------:|:---------:|
+| [deepvk/deberta-v1-distill](https://huggingface.co/deepvk/deberta-v1-distill)  | 0.433     |  0.56  | 0.625   | 0.590 | 0.943   | 0.569   | 0.726   | 0.635     |
+| [deepvk/deberta-v1-base](https://huggingface.co/deepvk/deberta-v1-base)        | 0.450     |  0.61  | 0.722   | 0.704 | 0.948   | 0.578   | **0.760**   | 0.682     |
+| [ai-forever/ruBert-base](https://huggingface.co/ai-forever/ruBert-base)        | 0.491     |  0.61  | 0.663   | 0.769 | 0.962   | 0.574   | 0.678   | 0.678     |
+| [deepvk/RuModernBERT-small](https://huggingface.co/deepvk/RuModernBERT-small)  | 0.555     |  **0.64**  | 0.746   | 0.593 | 0.930   | 0.574   | 0.743   | 0.683     |
+| deepvk/RuModernBERT-base [this]                                                | **0.556** |  0.61  | **0.857**   | **0.818** | **0.977**   | **0.583**   | 0.758   | **0.737**     |
+
+### Encodechka
+
+|                                                                                     | Model Size |   STS-B  | Paraphraser |   XNLI   | Sentiment | Toxicity | Inappropriateness |  Intents | IntentsX |  FactRu  |  RuDReC  |   Avg. S   |  Avg. S+W |
+|------------------------------------------------------------------------------------:|:----------:|:--------:|:-----------:|:--------:|:---------:|:--------:|:-----------------:|:--------:|:--------:|:--------:|:--------:|:----------:|:---------:|
+|         [cointegrated/rubert-tiny](https://huggingface.co/cointegrated/rubert-tiny) |    11.9M   |   0.66   |     0.53    | **0.40** |    0.71   |   0.89   |        0.68       |   0.70   | **0.58** |   0.24   |   0.34   |    0.645   |   0.575   |
+|       [deepvk/deberta-v1-distill](https://huggingface.co/deepvk/deberta-v1-distill) |    81.5M   | **0.70** |   **0.57**  |   0.38   |  **0.77** | **0.98** |        0.79       |   0.77   |   0.36   |   0.36   | **0.44** |    0.665   | **0.612** |
+|             [deepvk/deberta-v1-base](https://huggingface.co/deepvk/deberta-v1-base) |    124M    |   0.68   |     0.54    |   0.38   |    0.76   | **0.98** |      **0.80**     | **0.78** |   0.29   |   0.29   |   0.40   |    0.653   |   0.591   |
+|   [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) |    150M    |   0.50   |     0.29    |   0.36   |    0.64   |   0.79   |        0.62       |   0.59   |   0.10   |   0.22   |   0.20   |    0.486   |   0.431   |
+|             [ai-forever/ruBert-base](https://huggingface.co/ai-forever/ruBert-base) |    178M    |   0.67   |     0.53    |   0.39   |  **0.77** | **0.98** |        0.78       |   0.77   |   0.38   |    🥴    |    🥴    |    0.659   |    🥴    |
+| [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) |    180M    |   0.63   |     0.50    |   0.38   |    0.73   |   0.94   |        0.74       |   0.74   |   0.31   |    🥴    |    🥴    |    0.621   |    🥴    |
+|       [deepvk/RuModernBERT-small](https://huggingface.co/deepvk/RuModernBERT-small) |     35M    |   0.64   |     0.50    |   0.36   |    0.72   |   0.95   |        0.73       |   0.72   |   0.47   |   0.28   |   0.26   |    0.636   |   0.563   |
+|                                                     deepvk/RuModernBERT-base [this] |    150M    |   0.67   |     0.54    |   0.35   |    0.75   |   0.97   |        0.76       |   0.76   | **0.58** | **0.37** |   0.36   | **0.673**  |   0.611   |
+
+## Citation
+
+```
+@misc{deepvk2025rumodernbert,
+    title={RuModernBERT: Modernized BERT for Russian},
+    author={Spirin, Egor and Malashenko, Boris and Sokolov Andrey},
+    url={https://huggingface.co/deepvk/rumodernbert-base},
+    publisher={Hugging Face}
+    year={2025},
+}
+```

config.json

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+{
+  "activation_function": "gelu",
+  "allow_embedding_resizing": true,
+  "architectures": [
+    "ModernBertForMaskedLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attention_layer": "rope",
+  "attention_probs_dropout_prob": 0.0,
+  "attn_out_bias": false,
+  "attn_out_dropout_prob": 0.1,
+  "attn_qkv_bias": false,
+  "bert_layer": "prenorm",
+  "bos_token_id": 50281,
+  "classifier_activation": "gelu",
+  "classifier_bias": false,
+  "classifier_dropout": 0.0,
+  "classifier_pooling": "cls",
+  "cls_token_id": 50281,
+  "compile_model": true,
+  "decoder_bias": true,
+  "deterministic_flash_attn": false,
+  "embed_dropout_prob": 0.0,
+  "embed_norm": true,
+  "embedding_dropout": 0.0,
+  "embedding_layer": "sans_pos",
+  "eos_token_id": 50282,
+  "final_norm": true,
+  "global_attn_every_n_layers": 3,
+  "global_rope_theta": 160000.0,
+  "head_pred_act": "gelu",
+  "hidden_act": "gelu",
+  "hidden_activation": "gelu",
+  "hidden_size": 768,
+  "init_method": "full_megatron",
+  "initializer_cutoff_factor": 2.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 1152,
+  "local_attention": 128,
+  "local_attn_rotary_emb_base": 10000.0,
+  "local_rope_theta": 10000.0,
+  "loss_function": "fa_cross_entropy",
+  "loss_kwargs": {
+    "reduction": "mean"
+  },
+  "masked_prediction": true,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "mlp_dropout": 0.0,
+  "mlp_dropout_prob": 0.0,
+  "mlp_in_bias": false,
+  "mlp_layer": "glu",
+  "mlp_out_bias": false,
+  "model_type": "modernbert",
+  "norm_bias": false,
+  "norm_eps": 1e-05,
+  "norm_kwargs": {
+    "bias": false,
+    "eps": 1e-05
+  },
+  "normalization": "layernorm",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 22,
+  "pad_token_id": 50283,
+  "padding": "unpadded",
+  "reference_compile": false,
+  "repad_logits_with_grad": false,
+  "rotary_emb_base": 160000.0,
+  "rotary_emb_dim": null,
+  "rotary_emb_interleaved": false,
+  "rotary_emb_scale_base": null,
+  "sep_token_id": 50282,
+  "skip_first_prenorm": true,
+  "sliding_window": 128,
+  "sparse_pred_ignore_index": -100,
+  "sparse_prediction": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.1",
+  "unpad_embeddings": true,
+  "vocab_size": 50368
+}

model.safetensors

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special_tokens_map.json

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tokenizer_config.json

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