Training complete

README.md

@@ -26,16 +26,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9363606231355651
+      value: 0.9363711681855841
     - name: Recall
       type: recall
-      value: 0.9508582968697409
+      value: 0.9510265903736116
     - name: F1
       type: f1
-      value: 0.9435537742150969
+      value: 0.9436419804625532
     - name: Accuracy
       type: accuracy
-      value: 0.9867251427562254
+      value: 0.9866809913463237
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -45,9 +45,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0616
+- Loss: 0.0628
 - Precision: 0.9364
-- Recall: 0.9509
+- Recall: 0.9510
 - F1: 0.9436
 - Accuracy: 0.9867
 
@@ -72,7 +72,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- 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: linear
 - num_epochs: 3
 
@@ -80,14 +80,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0771        | 1.0   | 1756 | 0.0683          | 0.9056    | 0.9297 | 0.9175 | 0.9816   |
-| 0.0346        | 2.0   | 3512 | 0.0669          | 0.9318    | 0.9448 | 0.9382 | 0.9850   |
-| 0.0231        | 3.0   | 5268 | 0.0616          | 0.9364    | 0.9509 | 0.9436 | 0.9867   |
+| 0.0799        | 1.0   | 1756 | 0.0664          | 0.9072    | 0.9325 | 0.9197 | 0.9823   |
+| 0.0354        | 2.0   | 3512 | 0.0655          | 0.9334    | 0.9480 | 0.9406 | 0.9860   |
+| 0.0222        | 3.0   | 5268 | 0.0628          | 0.9364    | 0.9510 | 0.9436 | 0.9867   |
 
 
 ### Framework versions
 
-- Transformers 4.45.2
-- Pytorch 2.5.0
-- Datasets 3.0.1
-- Tokenizers 0.20.0
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu124
+- Datasets 3.1.0
+- Tokenizers 0.20.1

runs/Nov09_18-48-01_p16/events.out.tfevents.1731149289.p16.969408.0

@@ -1,3 +1,3 @@
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-size 8436
+oid sha256:afd85ba901ffbd42465bf001ac29fea421b8f8cb934055c4a3883d746d1a9ce7
+size 9262