End of training

README.md

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+---
+base_model: ai-forever/ruBert-large
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: ruBert-large_ner
+  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. -->
+
+# ruBert-large_ner
+
+This model is a fine-tuned version of [ai-forever/ruBert-large](https://huggingface.co/ai-forever/ruBert-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5158
+- Precision: 0.8832
+- Recall: 0.9014
+- F1: 0.8912
+- Accuracy: 0.9234
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 438  | 0.3216          | 0.8700    | 0.8309 | 0.8448 | 0.8941   |
+| 0.3915        | 2.0   | 876  | 0.3379          | 0.8596    | 0.8790 | 0.8672 | 0.9089   |
+| 0.175         | 3.0   | 1314 | 0.3441          | 0.8656    | 0.8833 | 0.8737 | 0.9092   |
+| 0.0942        | 4.0   | 1752 | 0.3751          | 0.8651    | 0.8856 | 0.8729 | 0.9104   |
+| 0.0597        | 5.0   | 2190 | 0.3919          | 0.8881    | 0.9002 | 0.8935 | 0.9236   |
+| 0.0309        | 6.0   | 2628 | 0.4360          | 0.8730    | 0.8958 | 0.8821 | 0.9171   |
+| 0.0154        | 7.0   | 3066 | 0.4564          | 0.8848    | 0.8985 | 0.8907 | 0.9234   |
+| 0.0064        | 8.0   | 3504 | 0.4809          | 0.8797    | 0.9036 | 0.8904 | 0.9236   |
+| 0.0064        | 9.0   | 3942 | 0.5027          | 0.8832    | 0.9024 | 0.8917 | 0.9232   |
+| 0.0024        | 10.0  | 4380 | 0.5158          | 0.8832    | 0.9014 | 0.8912 | 0.9234   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "ai-forever/ruBert-large",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 120138
+}

model.safetensors

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+size 1703512036

training_args.bin

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