End of training

README.md

@@ -1,6 +1,6 @@
 ---
 license: apache-2.0
-base_model: distilbert-base-uncased
+base_model: distilbert-base-cased
 tags:
 - generated_from_trainer
 datasets:
@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9624574848236965
+      value: 0.963972882815022
     - name: Recall
       type: recall
-      value: 0.9300632384756199
+      value: 0.9317482110168082
     - name: F1
       type: f1
-      value: 0.9459831157565114
+      value: 0.9475866591916392
     - name: Accuracy
       type: accuracy
-      value: 0.9665913020348451
+      value: 0.9675355765394335
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -42,13 +42,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Bert-NER
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the ner dataset.
+This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the ner dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0764
-- Precision: 0.9625
-- Recall: 0.9301
-- F1: 0.9460
-- Accuracy: 0.9666
+- Loss: 0.0729
+- Precision: 0.9640
+- Recall: 0.9317
+- F1: 0.9476
+- Accuracy: 0.9675
 
 ## Model description
 
@@ -67,7 +67,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 6e-05
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
@@ -79,9 +79,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 438  | 0.0869          | 0.9598    | 0.9263 | 0.9427 | 0.9648   |
-| 0.0834        | 2.0   | 876  | 0.0815          | 0.9627    | 0.9280 | 0.9450 | 0.9661   |
-| 0.054         | 3.0   | 1314 | 0.0764          | 0.9625    | 0.9301 | 0.9460 | 0.9666   |
+| No log        | 1.0   | 438  | 0.0865          | 0.9568    | 0.9243 | 0.9403 | 0.9632   |
+| 0.0768        | 2.0   | 876  | 0.0794          | 0.9635    | 0.9277 | 0.9452 | 0.9662   |
+| 0.0515        | 3.0   | 1314 | 0.0729          | 0.9640    | 0.9317 | 0.9476 | 0.9675   |
 
 
 ### Framework versions