End of training

README.md

@@ -1,9 +1,8 @@
 ---
 license: apache-2.0
+base_model: distilbert-base-uncased
 tags:
 - generated_from_trainer
-datasets:
-- conll2003
 metrics:
 - precision
 - recall
@@ -11,27 +10,7 @@ metrics:
 - accuracy
 model-index:
 - name: distilbert-base-uncased-finetuned-ner
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: conll2003
-      type: conll2003
-      args: conll2003
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.9244616234124793
-    - name: Recall
-      type: recall
-      value: 0.9364582168027744
-    - name: F1
-      type: f1
-      value: 0.9304212515282871
-    - name: Accuracy
-      type: accuracy
-      value: 0.9833987322668276
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -39,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # distilbert-base-uncased-finetuned-ner
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0623
-- Precision: 0.9245
-- Recall: 0.9365
-- F1: 0.9304
-- Accuracy: 0.9834
+- Loss: 0.0601
+- Precision: 0.9229
+- Recall: 0.9352
+- F1: 0.9290
+- Accuracy: 0.9831
 
 ## Model description
 
@@ -76,14 +55,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.2377        | 1.0   | 878  | 0.0711          | 0.9176    | 0.9254 | 0.9215 | 0.9813   |
-| 0.0514        | 2.0   | 1756 | 0.0637          | 0.9213    | 0.9346 | 0.9279 | 0.9831   |
-| 0.031         | 3.0   | 2634 | 0.0623          | 0.9245    | 0.9365 | 0.9304 | 0.9834   |
+| 0.2538        | 1.0   | 878  | 0.0725          | 0.8985    | 0.9165 | 0.9074 | 0.9792   |
+| 0.0514        | 2.0   | 1756 | 0.0593          | 0.9218    | 0.9318 | 0.9267 | 0.9827   |
+| 0.0308        | 3.0   | 2634 | 0.0601          | 0.9229    | 0.9352 | 0.9290 | 0.9831   |
 
 
 ### Framework versions
 
-- Transformers 4.12.5
-- Pytorch 1.10.0+cu111
-- Datasets 1.16.1
-- Tokenizers 0.10.3
+- Transformers 4.36.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.0
+- Tokenizers 0.15.0

model.safetensors

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runs/Dec25_14-01-00_2e15fbdb4865/events.out.tfevents.1703512861.2e15fbdb4865.942.0

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runs/Dec25_14-01-00_2e15fbdb4865/events.out.tfevents.1703513127.2e15fbdb4865.942.1

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