borisMI/chgk_ner

README.md

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+---
+library_name: transformers
+base_model: ai-forever/ruBert-large
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: my-chgk-ner-model-v1
+  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. -->
+
+# my-chgk-ner-model-v1
+
+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: 0.3204
+- Precision: 0.6308
+- Recall: 0.6464
+- F1: 0.6347
+
+## 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: 16
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 25
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 50   | 0.2016          | 0.3892    | 0.4330 | 0.3974 |
+| No log        | 2.0   | 100  | 0.1674          | 0.4990    | 0.5723 | 0.5258 |
+| No log        | 3.0   | 150  | 0.1732          | 0.5184    | 0.6257 | 0.5621 |
+| No log        | 4.0   | 200  | 0.1819          | 0.5821    | 0.6373 | 0.6079 |
+| No log        | 5.0   | 250  | 0.2041          | 0.6160    | 0.6317 | 0.6208 |
+| No log        | 6.0   | 300  | 0.2197          | 0.6023    | 0.6908 | 0.6411 |
+| No log        | 7.0   | 350  | 0.2349          | 0.6100    | 0.6512 | 0.6281 |
+| No log        | 8.0   | 400  | 0.2418          | 0.6039    | 0.6490 | 0.6240 |
+| No log        | 9.0   | 450  | 0.2609          | 0.6456    | 0.6744 | 0.6575 |
+| 0.0914        | 10.0  | 500  | 0.2792          | 0.6243    | 0.6658 | 0.6396 |
+| 0.0914        | 11.0  | 550  | 0.2931          | 0.6375    | 0.6693 | 0.6515 |
+| 0.0914        | 12.0  | 600  | 0.3204          | 0.6308    | 0.6464 | 0.6347 |
+
+
+### Framework versions
+
+- Transformers 4.52.4
+- Pytorch 2.6.0+cu124
+- Datasets 3.6.0
+- Tokenizers 0.21.2

best_model/config.json

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+{
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+    "BertForTokenClassification"
+  ],
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+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "B-AUTHOR",
+    "1": "I-AUTHOR",
+    "2": "B-CHARACTER",
+    "3": "I-CHARACTER",
+    "4": "B-LOCATION",
+    "5": "I-LOCATION",
+    "6": "B-PERSON",
+    "7": "I-PERSON",
+    "8": "B-WORK_OF_ART",
+    "9": "I-WORK_OF_ART",
+    "10": "O"
+  },
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+  "intermediate_size": 4096,
+  "label2id": {
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+    "B-PERSON": 6,
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+    "I-PERSON": 7,
+    "I-WORK_OF_ART": 9,
+    "O": 10
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+  "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": "4.52.4",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 120138
+}

best_model/model.safetensors

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best_model/special_tokens_map.json

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best_model/tokenizer_config.json

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+}

best_model/training_args.bin

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config.json

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+  "directionality": "bidi",
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+  "id2label": {
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+    "6": "B-PERSON",
+    "7": "I-PERSON",
+    "8": "B-WORK_OF_ART",
+    "9": "I-WORK_OF_ART",
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+  "label2id": {
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model.safetensors

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special_tokens_map.json

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tokenizer_config.json

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