Model save

README.md

@@ -3,6 +3,11 @@ license: bigscience-openrail-m
 base_model: ehsanaghaei/SecureBERT
 tags:
 - generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: SecureBERT-finetuned-ner
   results: []
@@ -15,16 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [ehsanaghaei/SecureBERT](https://huggingface.co/ehsanaghaei/SecureBERT) on the None dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.3307
-- eval_precision: 0.8102
-- eval_recall: 0.8412
-- eval_f1: 0.8254
-- eval_accuracy: 0.9269
-- eval_runtime: 7.8038
-- eval_samples_per_second: 153.386
-- eval_steps_per_second: 38.443
-- epoch: 5.0
-- step: 11975
+- Loss: 0.4660
+- Precision: 0.8270
+- Recall: 0.8429
+- F1: 0.8349
+- Accuracy: 0.9309
 
 ## Model description
 
@@ -49,7 +49,18 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 20
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1046        | 1.0   | 2395  | 0.3706          | 0.8023    | 0.8288 | 0.8153 | 0.9250   |
+| 0.0707        | 2.0   | 4790  | 0.3917          | 0.8138    | 0.8415 | 0.8274 | 0.9297   |
+| 0.0551        | 3.0   | 7185  | 0.4256          | 0.8220    | 0.8374 | 0.8296 | 0.9293   |
+| 0.0371        | 4.0   | 9580  | 0.4476          | 0.8293    | 0.8406 | 0.8349 | 0.9306   |
+| 0.0265        | 5.0   | 11975 | 0.4660          | 0.8270    | 0.8429 | 0.8349 | 0.9309   |
+
 
 ### Framework versions
 

runs/Jul30_08-27-44_060c39296710/events.out.tfevents.1722328069.060c39296710.943.1

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-size 15422
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+size 16248

runs/Jul30_08-27-44_060c39296710/events.out.tfevents.1722330254.060c39296710.943.2

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