End of training

README.md

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+---
+base_model: klue/roberta-large
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: klue-roberta-large-ner-identified
+  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. -->
+
+# klue-roberta-large-ner-identified
+
+This model is a fine-tuned version of [klue/roberta-large](https://huggingface.co/klue/roberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0044
+- Precision: 0.9920
+- Recall: 0.9977
+- F1: 0.9948
+- Accuracy: 0.9990
+
+## 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: 64
+- eval_batch_size: 64
+- 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 | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 61   | 0.0093          | 0.9807    | 0.9931 | 0.9869 | 0.9981   |
+| No log        | 2.0   | 122  | 0.0065          | 0.9874    | 0.9931 | 0.9903 | 0.9984   |
+| No log        | 3.0   | 183  | 0.0044          | 0.9920    | 0.9977 | 0.9948 | 0.9990   |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.0+cu118
+- Datasets 2.19.1
+- Tokenizers 0.19.1