Fine-tuning Complete

README.md

@@ -5,28 +5,9 @@ tags:
 - generated_from_trainer
 datasets:
 - emotion
-metrics:
-- accuracy
-- f1
 model-index:
 - name: distilbert-base-uncased-finetuned-emotion
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: emotion
-      type: emotion
-      config: split
-      split: validation
-      args: split
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.931
-    - name: F1
-      type: f1
-      value: 0.9313351347991748
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,10 +16,6 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-base-uncased-finetuned-emotion
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1701
-- Accuracy: 0.931
-- F1: 0.9313
 
 ## Model description
 
@@ -58,21 +35,13 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 64
+- eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 2
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.2675        | 1.0   | 500  | 0.2337          | 0.921    | 0.9213 |
-| 0.1703        | 2.0   | 1000 | 0.1701          | 0.931    | 0.9313 |
-
-
 ### Framework versions
 
 - Transformers 4.34.1

training_args.bin

@@ -1,3 +1,3 @@
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