End of training

README.md

@@ -1,8 +1,12 @@
 ---
-license: mit
-base_model: FacebookAI/xlm-roberta-base
+base_model: NlpHUST/ner-vietnamese-electra-base
 tags:
 - generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: my_awesome_ner-token_classification_v1.0
   results: []
@@ -13,18 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # my_awesome_ner-token_classification_v1.0
 
-This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
+This model is a fine-tuned version of [NlpHUST/ner-vietnamese-electra-base](https://huggingface.co/NlpHUST/ner-vietnamese-electra-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.8037
-- eval_precision: 0.4696
-- eval_recall: 0.5214
-- eval_f1: 0.4941
-- eval_accuracy: 0.7969
-- eval_runtime: 6.2464
-- eval_samples_per_second: 80.046
-- eval_steps_per_second: 5.123
-- epoch: 9.9645
-- step: 2810
+- Loss: 1.0322
+- Precision: 0.4590
+- Recall: 0.5400
+- F1: 0.4963
+- Accuracy: 0.7805
 
 ## Model description
 
@@ -51,6 +50,20 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: cosine
 - num_epochs: 20
 
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.8701        | 1.9929  | 562  | 0.8431          | 0.4537    | 0.4154 | 0.4337 | 0.7907   |
+| 0.5651        | 3.9858  | 1124 | 0.7613          | 0.4524    | 0.4899 | 0.4704 | 0.7898   |
+| 0.4312        | 5.9787  | 1686 | 0.8134          | 0.4654    | 0.5182 | 0.4904 | 0.7902   |
+| 0.3305        | 7.9716  | 2248 | 0.8743          | 0.4417    | 0.5336 | 0.4833 | 0.7762   |
+| 0.255         | 9.9645  | 2810 | 0.9331          | 0.4217    | 0.5375 | 0.4726 | 0.7694   |
+| 0.2071        | 11.9574 | 3372 | 0.9707          | 0.4527    | 0.5435 | 0.4940 | 0.7795   |
+| 0.1984        | 13.9504 | 3934 | 0.9967          | 0.4663    | 0.5336 | 0.4977 | 0.7834   |
+| 0.1702        | 15.9433 | 4496 | 1.0322          | 0.4590    | 0.5400 | 0.4963 | 0.7805   |
+
+
 ### Framework versions
 
 - Transformers 4.41.2