Training complete

README.md

@@ -1,8 +1,10 @@
 ---
-license: apache-2.0
-base_model: bert-base-cased
+license: mit
+base_model: microsoft/llmlingua-2-xlm-roberta-large-meetingbank
 tags:
 - generated_from_trainer
+datasets:
+- conll2003
 metrics:
 - precision
 - recall
@@ -10,7 +12,29 @@ metrics:
 - accuracy
 model-index:
 - name: bert-finetuned-ner
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      config: conll2003
+      split: validation
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9570808283233133
+    - name: Recall
+      type: recall
+      value: 0.9644900706832716
+    - name: F1
+      type: f1
+      value: 0.9607711651299247
+    - name: Accuracy
+      type: accuracy
+      value: 0.9922812683901517
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,13 +42,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert-finetuned-ner
 
-This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
+This model is a fine-tuned version of [microsoft/llmlingua-2-xlm-roberta-large-meetingbank](https://huggingface.co/microsoft/llmlingua-2-xlm-roberta-large-meetingbank) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0821
-- Precision: 0.9403
-- Recall: 0.9539
-- F1: 0.9470
-- Accuracy: 0.9866
+- Loss: 0.0434
+- Precision: 0.9571
+- Recall: 0.9645
+- F1: 0.9608
+- Accuracy: 0.9923
 
 ## Model description
 
@@ -55,9 +79,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.017         | 1.0   | 1756 | 0.0783          | 0.9261    | 0.9387 | 0.9324 | 0.9839   |
-| 0.0109        | 2.0   | 3512 | 0.0775          | 0.9336    | 0.9495 | 0.9415 | 0.9857   |
-| 0.0058        | 3.0   | 5268 | 0.0821          | 0.9403    | 0.9539 | 0.9470 | 0.9866   |
+| 0.0716        | 1.0   | 1756 | 0.0592          | 0.9321    | 0.9468 | 0.9394 | 0.9885   |
+| 0.0344        | 2.0   | 3512 | 0.0518          | 0.9507    | 0.9581 | 0.9544 | 0.9908   |
+| 0.0213        | 3.0   | 5268 | 0.0434          | 0.9571    | 0.9645 | 0.9608 | 0.9923   |
 
 
 ### Framework versions

model.safetensors

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+oid sha256:634f5244b216fb044ffcb12f26bbf65fbfd650976971609aa241c3d7b1932384
 size 2235858356

runs/Apr09_00-26-18_ca836123dfb8/events.out.tfevents.1712622379.ca836123dfb8.444.0

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+oid sha256:0f67d87cd2f7ddc8ea4942af4066c99c0081d378bb771bed0f0641085968350c
+size 8899