End of training

README.md

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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

config.json

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+{
+  "_name_or_path": "cointegrated/rubert-tiny2",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "emb_size": 312,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 312,
+  "initializer_range": 0.02,
+  "intermediate_size": 600,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 2048,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 3,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 83828
+}

model.safetensors

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+size 116784136

special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 2048,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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