Training complete

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert/distilbert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distillbert-base-cased-finetuned-ner3
+  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. -->
+
+# distillbert-base-cased-finetuned-ner3
+
+This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1370
+- Precision: 0.7851
+- Recall: 0.8195
+- F1: 0.8020
+- Accuracy: 0.9579
+
+## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 7
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1896        | 1.0   | 4750  | 0.1830          | 0.7113    | 0.7623 | 0.7359 | 0.9457   |
+| 0.1468        | 2.0   | 9500  | 0.1514          | 0.7723    | 0.7932 | 0.7826 | 0.9532   |
+| 0.1321        | 3.0   | 14250 | 0.1421          | 0.7700    | 0.8050 | 0.7871 | 0.9557   |
+| 0.124         | 4.0   | 19000 | 0.1369          | 0.7771    | 0.8102 | 0.7933 | 0.9574   |
+| 0.1243        | 5.0   | 23750 | 0.1380          | 0.7815    | 0.8152 | 0.798  | 0.9572   |
+| 0.1129        | 6.0   | 28500 | 0.1371          | 0.7862    | 0.8188 | 0.8022 | 0.9577   |
+| 0.1138        | 7.0   | 33250 | 0.1370          | 0.7851    | 0.8195 | 0.8020 | 0.9579   |
+
+
+### Framework versions
+
+- Transformers 4.50.1
+- Pytorch 2.5.1+cu124
+- Datasets 3.4.1
+- Tokenizers 0.21.1

model.safetensors

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