End of training

README.md

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+---
+license: apache-2.0
+base_model: ethanyt/guwenbert-large
+tags:
+- generated_from_trainer
+datasets:
+- ched_ner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: guwenbert-large-CHED-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: ched_ner
+      type: ched_ner
+      config: ched_ner
+      split: validation
+      args: ched_ner
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7442799461641992
+    - name: Recall
+      type: recall
+      value: 0.8069066147859922
+    - name: F1
+      type: f1
+      value: 0.7743290548424737
+    - name: Accuracy
+      type: accuracy
+      value: 0.9666064635130461
+---
+
+<!-- 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. -->
+
+# guwenbert-large-CHED-ner
+
+This model is a fine-tuned version of [ethanyt/guwenbert-large](https://huggingface.co/ethanyt/guwenbert-large) on the ched_ner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1905
+- Precision: 0.7443
+- Recall: 0.8069
+- F1: 0.7743
+- Accuracy: 0.9666
+
+## 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: 16
+- eval_batch_size: 16
+- 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   | 356  | 0.1420          | 0.6862    | 0.7573 | 0.72   | 0.9609   |
+| 0.2304        | 2.0   | 712  | 0.1324          | 0.6907    | 0.7972 | 0.7401 | 0.9624   |
+| 0.095         | 3.0   | 1068 | 0.1314          | 0.7268    | 0.7918 | 0.7579 | 0.9656   |
+| 0.095         | 4.0   | 1424 | 0.1348          | 0.7248    | 0.7967 | 0.7590 | 0.9659   |
+| 0.0613        | 5.0   | 1780 | 0.1525          | 0.7088    | 0.8147 | 0.7581 | 0.9635   |
+| 0.0397        | 6.0   | 2136 | 0.1635          | 0.7224    | 0.8127 | 0.7649 | 0.9648   |
+| 0.0397        | 7.0   | 2492 | 0.1693          | 0.7416    | 0.7986 | 0.7691 | 0.9662   |
+| 0.0261        | 8.0   | 2848 | 0.1809          | 0.7338    | 0.8059 | 0.7682 | 0.9657   |
+| 0.0164        | 9.0   | 3204 | 0.1904          | 0.7291    | 0.8127 | 0.7686 | 0.9655   |
+| 0.0124        | 10.0  | 3560 | 0.1905          | 0.7443    | 0.8069 | 0.7743 | 0.9666   |
+
+
+### Framework versions
+
+- Transformers 4.43.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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