End of training

README.md

@@ -26,16 +26,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.5535353535353535
+      value: 0.44532803180914515
     - name: Recall
       type: recall
-      value: 0.25393883225208524
+      value: 0.20759962928637626
     - name: F1
       type: f1
-      value: 0.34815756035578144
+      value: 0.28318584070796454
     - name: Accuracy
       type: accuracy
-      value: 0.9386088666581164
+      value: 0.9365140438630243
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -45,11 +45,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the wnut_17 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2889
-- Precision: 0.5535
-- Recall: 0.2539
-- F1: 0.3482
-- Accuracy: 0.9386
+- Loss: 0.2982
+- Precision: 0.4453
+- Recall: 0.2076
+- F1: 0.2832
+- Accuracy: 0.9365
 
 ## Model description
 
@@ -72,7 +72,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use 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: 2
 
@@ -80,13 +80,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 107  | 0.3084          | 0.4140    | 0.0825 | 0.1376 | 0.9310   |
-| No log        | 2.0   | 214  | 0.2889          | 0.5535    | 0.2539 | 0.3482 | 0.9386   |
+| No log        | 1.0   | 107  | 0.3151          | 0.3618    | 0.0825 | 0.1343 | 0.9310   |
+| No log        | 2.0   | 214  | 0.2982          | 0.4453    | 0.2076 | 0.2832 | 0.9365   |
 
 
 ### Framework versions
 
-- Transformers 4.44.2
+- Transformers 4.47.1
 - Pytorch 2.4.1+cu121
 - Datasets 3.2.0
-- Tokenizers 0.19.1
+- Tokenizers 0.21.0

runs/Dec22_08-03-58_0c07bf4a9517/events.out.tfevents.1734854640.0c07bf4a9517.6907.0

@@ -1,3 +1,3 @@
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-size 6006
+oid sha256:bcef60bcf712ab6e56dea38af21a905c93324d620bbf75e9001d787d59cdec31
+size 6832