Initial commit

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert-base-cased-ru-cola_32_3e-05_lr_0.1_decay_balanced
+  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. -->
+
+# bert-base-cased-ru-cola_32_3e-05_lr_0.1_decay_balanced
+
+This model is a fine-tuned version of [sberbank-ai/ruBert-base](https://huggingface.co/sberbank-ai/ruBert-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5267
+- Accuracy: 0.8026
+- Mcc: 0.4195
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.27.0.dev0
+- Pytorch 1.13.1+cu116
+- Datasets 2.9.0
+- Tokenizers 0.13.2

all_results.json

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+{
+    "epoch": 5.0,
+    "eval_accuracy": 0.8026449643947101,
+    "eval_loss": 1.526693344116211,
+    "eval_mcc": 0.4195472854640705,
+    "eval_runtime": 2.2172,
+    "eval_samples": 983,
+    "eval_samples_per_second": 443.362,
+    "eval_steps_per_second": 55.477,
+    "train_loss": 0.26801115826862615,
+    "train_runtime": 238.2502,
+    "train_samples": 7869,
+    "train_samples_per_second": 165.141,
+    "train_steps_per_second": 5.163
+}

config.json

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+{
+  "_name_or_path": "sberbank-ai/ruBert-base",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": 0,
+    "1": 1
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "0": 0,
+    "1": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.27.0.dev0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 120138
+}

eval_results.json

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+{
+    "epoch": 5.0,
+    "eval_accuracy": 0.8026449643947101,
+    "eval_loss": 1.526693344116211,
+    "eval_mcc": 0.4195472854640705,
+    "eval_runtime": 2.2172,
+    "eval_samples": 983,
+    "eval_samples_per_second": 443.362,
+    "eval_steps_per_second": 55.477
+}

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predict_results_test.txt

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predict_results_train.txt

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