Completed training

README.md

@@ -8,20 +8,20 @@ metrics:
 - accuracy
 - f1
 model-index:
-- name: classifier-chapter4
+- name: assignment1_DestilBert
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# classifier-chapter4
+# assignment1_DestilBert
 
 This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2475
-- Accuracy: 0.9166
-- F1: 0.9165
+- Loss: 0.2442
+- Accuracy: 0.9191
+- F1: 0.9191
 
 ## Model description
 
@@ -41,8 +41,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 64
-- eval_batch_size: 64
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
@@ -52,8 +52,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 157  | 0.2769          | 0.9087   | 0.9083 |
-| No log        | 2.0   | 314  | 0.2475          | 0.9166   | 0.9165 |
+| No log        | 1.0   | 313  | 0.2607          | 0.9118   | 0.9116 |
+| 0.3049        | 2.0   | 626  | 0.2442          | 0.9191   | 0.9191 |
 
 
 ### Framework versions