End of training

README.md

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+---
+license: mit
+base_model: r1char9/rubert-base-cased-russian-sentiment
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: ru_sentiment_classification_model
+  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. -->
+
+# ru_sentiment_classification_model
+
+This model is a fine-tuned version of [r1char9/rubert-base-cased-russian-sentiment](https://huggingface.co/r1char9/rubert-base-cased-russian-sentiment) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8975
+- Accuracy: 0.72
+- Precision: 0.7047
+- Recall: 0.72
+- F1: 0.7086
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 13   | 0.6573          | 0.7      | 0.6577    | 0.7    | 0.6561 |
+| No log        | 2.0   | 26   | 0.8104          | 0.71     | 0.6912    | 0.71   | 0.6956 |
+| No log        | 3.0   | 39   | 0.8975          | 0.72     | 0.7047    | 0.72   | 0.7086 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "r1char9/rubert-base-cased-russian-sentiment",
+  "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": "neutral",
+    "1": "positive",
+    "2": "negative"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "negative": 2,
+    "neutral": 0,
+    "positive": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "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": "4.38.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 119547
+}

model.safetensors

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runs/Apr22_14-02-05_6d1c6b346db0/events.out.tfevents.1713794527.6d1c6b346db0.674.1

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training_args.bin

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