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README.md

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 ---
 license: mit
+pipeline_tag: text-generation
+widget:
+- text: "@@ПЕРВЫЙ@@ привет @@ВТОРОЙ@@ привет @@ПЕРВЫЙ@@ как дела? @@ВТОРОЙ@@"
+  example_title: "how r u"
+- text: "@@ПЕРВЫЙ@@ что ты делал на выходных? @@ВТОРОЙ@@"
+  example_title: "wyd"
+language:
+- ru
+tags:
+- conversational
 ---
+This generation model is based on [sberbank-ai/rugpt3medium_based_on_gpt2](https://huggingface.co/sberbank-ai/rugpt3medium_based_on_gpt2). It's trained on large corpus of dialog data and can be used for buildning generative conversational agents
+
+The model was trained with context size 3
+
+
+On a validation set we calculated metrics introduced in [this paper](https://arxiv.org/pdf/2001.09977.pdf): 
+- Sensibleness: Operators are asked whether model's response makes sense given the context
+- Specificity: Operators are asked whether model's response is specific for given context, in other words we don't want our model to give general and boring responses
+- SSA which is the average of two metrics above (Sensibleness Specificity Average)
+
+|                                                     |   sensibleness |   specificity |   SSA |
+|:----------------------------------------------------|---------------:|--------------:|------:|
+| [tinkoff-ai/ruDialoGPT-small](https://huggingface.co/tinkoff-ai/ruDialoGPT-small)  |           0.64 |          0.5  | 0.57  |
+| [tinkoff-ai/ruDialoGPT-medium](https://huggingface.co/tinkoff-ai/ruDialoGPT-medium) |           0.78 |          0.69 | 0.735 |
+
+
+How to use:
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelWithLMHead
+
+tokenizer = AutoTokenizer.from_pretrained('tinkoff-ai/ruDialoGPT-medium')
+model = AutoModelWithLMHead.from_pretrained('tinkoff-ai/ruDialoGPT-medium')
+inputs = tokenizer('@@ПЕРВЫЙ@@ привет @@ВТОРОЙ@@ привет @@ПЕРВЫЙ@@ как дела? @@ВТОРОЙ@@', return_tensors='pt')
+with torch.inference_mode():
+    generated_token_ids = model.generate(**inputs)
+    context_with_response = tokenizer.decode(generated_token_ids[0])
+context_with_response
+```

added_tokens.json

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+{"@@ПЕРВЫЙ@@": 50257, "@@ВТОРОЙ@@": 50258, "<FIRST_SPEAKER>": 50259, "<SECOND_SPEAKER>": 50260}

all_results.json

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+{
+    "epoch": 1.0,
+    "eval_loss": 3.4997777938842773,
+    "eval_runtime": 448.829,
+    "eval_samples": 40311,
+    "eval_samples_per_second": 89.814,
+    "eval_steps_per_second": 7.486,
+    "perplexity": 33.10809432022858,
+    "train_loss": 3.4927627832876236,
+    "train_runtime": 361845.2402,
+    "train_samples": 8570756,
+    "train_samples_per_second": 23.686,
+    "train_steps_per_second": 1.974
+}

config.json

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+{
+  "activation_function": "gelu_new",
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 2048,
+  "n_embd": 1024,
+  "n_head": 16,
+  "n_inner": null,
+  "n_layer": 24,
+  "n_positions": 2048,
+  "n_special": 0,
+  "output_past": true,
+  "predict_special_tokens": true,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.15.0",
+  "use_cache": true,
+  "vocab_size": 50261
+}

eval_results.json

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+{
+    "epoch": 1.0,
+    "eval_loss": 3.4997777938842773,
+    "eval_runtime": 448.829,
+    "eval_samples": 40311,
+    "eval_samples_per_second": 89.814,
+    "eval_steps_per_second": 7.486,
+    "perplexity": 33.10809432022858
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:63c43b3834b279073e85862dddf924c2c961ba882a1e34fdb1008e2e353dff3b
+size 1524289497

special_tokens_map.json

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+{"bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": "<pad>"}

tokenizer_config.json

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+{"errors": "replace", "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "special_tokens_map_file": null, "use_fast": true, "tokenizer_class": "GPT2Tokenizer"}

train_results.json

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+{
+    "epoch": 1.0,
+    "train_loss": 3.4927627832876236,
+    "train_runtime": 361845.2402,
+    "train_samples": 8570756,
+    "train_samples_per_second": 23.686,
+    "train_steps_per_second": 1.974
+}