End of training

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.5727002967359051
+      value: 0.5720930232558139
     - name: Recall
       type: recall
-      value: 0.3577386468952734
+      value: 0.34198331788693237
     - name: F1
       type: f1
-      value: 0.44038790644609244
+      value: 0.4280742459396752
     - name: Accuracy
       type: accuracy
-      value: 0.9460476251549741
+      value: 0.9453636013851482
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wnut_17 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2710
-- Precision: 0.5727
-- Recall: 0.3577
-- F1: 0.4404
-- Accuracy: 0.9460
+- Loss: 0.3526
+- Precision: 0.5721
+- Recall: 0.3420
+- F1: 0.4281
+- Accuracy: 0.9454
 
 ## Model description
 
@@ -73,14 +73,16 @@ 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: 2
+- num_epochs: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 107  | 0.2573          | 0.4985    | 0.3160 | 0.3868 | 0.9413   |
-| No log        | 2.0   | 214  | 0.2710          | 0.5727    | 0.3577 | 0.4404 | 0.9460   |
+| No log        | 1.0   | 107  | 0.2863          | 0.3981    | 0.3494 | 0.3722 | 0.9328   |
+| No log        | 2.0   | 214  | 0.3438          | 0.5734    | 0.3151 | 0.4067 | 0.9443   |
+| No log        | 3.0   | 321  | 0.3482          | 0.5922    | 0.3216 | 0.4168 | 0.9445   |
+| No log        | 4.0   | 428  | 0.3526          | 0.5721    | 0.3420 | 0.4281 | 0.9454   |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
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+oid sha256:cd9dc644da4e4c2626b2c0e30419b205165bf2ae621fa47922704761c067a5ed
 size 265503852