my_models_best_1111

README.md

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+---
+library_name: transformers
+license: mit
+base_model: akdeniz27/bert-base-turkish-cased-ner
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: results
+  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. -->
+
+# results
+
+This model is a fine-tuned version of [akdeniz27/bert-base-turkish-cased-ner](https://huggingface.co/akdeniz27/bert-base-turkish-cased-ner) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 8.5343
+- Accuracy: 0.1071
+- F1: 0.1212
+- Classification Report:               precision    recall  f1-score   support
+
+        DATE       0.07      0.67      0.13         3
+    LOCATION       0.00      0.00      0.00         1
+      PERSON       0.00      0.00      0.00         1
+
+   micro avg       0.07      0.40      0.12         5
+   macro avg       0.02      0.22      0.04         5
+weighted avg       0.04      0.40      0.08         5
+
+
+## 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: 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Classification Report                                                                                                                                                                                                                                                                                                                                                                        |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 1    | 10.3125         | 0.1071   | 0.1212 |               precision    recall  f1-score   support
+
+        DATE       0.07      0.67      0.13         3
+    LOCATION       0.00      0.00      0.00         1
+      PERSON       0.00      0.00      0.00         1
+
+   micro avg       0.07      0.40      0.12         5
+   macro avg       0.02      0.22      0.04         5
+weighted avg       0.04      0.40      0.08         5
+ |
+| No log        | 2.0   | 2    | 9.1622          | 0.1071   | 0.1212 |               precision    recall  f1-score   support
+
+        DATE       0.07      0.67      0.13         3
+    LOCATION       0.00      0.00      0.00         1
+      PERSON       0.00      0.00      0.00         1
+
+   micro avg       0.07      0.40      0.12         5
+   macro avg       0.02      0.22      0.04         5
+weighted avg       0.04      0.40      0.08         5
+ |
+| No log        | 3.0   | 3    | 8.5343          | 0.1071   | 0.1212 |               precision    recall  f1-score   support
+
+        DATE       0.07      0.67      0.13         3
+    LOCATION       0.00      0.00      0.00         1
+      PERSON       0.00      0.00      0.00         1
+
+   micro avg       0.07      0.40      0.12         5
+   macro avg       0.02      0.22      0.04         5
+weighted avg       0.04      0.40      0.08         5
+ |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "akdeniz27/bert-base-turkish-cased-ner",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-PER",
+    "2": "I-PER",
+    "3": "B-ORG",
+    "4": "I-ORG",
+    "5": "B-LOC",
+    "6": "I-LOC"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-LOC": 5,
+    "B-ORG": 3,
+    "B-PER": 1,
+    "I-LOC": 6,
+    "I-ORG": 4,
+    "I-PER": 2,
+    "O": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32000
+}

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training_args.bin

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