End of training

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: transformers
 license: apache-2.0
-base_model: distilbert/distilbert-base-uncased
+base_model: ae-314/token_classification_wnut_model
 tags:
 - generated_from_trainer
 metrics:
@@ -19,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # token_classification_wnut_model
 
-This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
+This model is a fine-tuned version of [ae-314/token_classification_wnut_model](https://huggingface.co/ae-314/token_classification_wnut_model) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2820
-- Precision: 0.5582
-- Recall: 0.3021
-- F1: 0.3921
-- Accuracy: 0.9407
+- Loss: 0.2996
+- Precision: 0.5214
+- Recall: 0.3948
+- F1: 0.4494
+- Accuracy: 0.9458
 
 ## Model description
 
@@ -44,7 +44,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 3e-05
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
@@ -56,8 +56,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 213  | 0.2921          | 0.5582    | 0.2178 | 0.3133 | 0.9370   |
-| No log        | 2.0   | 426  | 0.2820          | 0.5582    | 0.3021 | 0.3921 | 0.9407   |
+| No log        | 1.0   | 213  | 0.2914          | 0.4222    | 0.3976 | 0.4095 | 0.9424   |
+| No log        | 2.0   | 426  | 0.2996          | 0.5214    | 0.3948 | 0.4494 | 0.9458   |
 
 
 ### Framework versions

runs/Oct18_06-04-56_b1d7bac1bef8/events.out.tfevents.1760767496.b1d7bac1bef8.678.8

@@ -1,3 +1,3 @@
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+size 6850