Update README.md

README.md

@@ -14,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # beit-sketch-classifier
 
-This model is a version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) fine-tuned on a dataset of Quick!Draw! sketches ([1 percent of the 50M sketches](https://huggingface.co/datasets/kmewhort/quickdraw-bins-1pct-sample)).
+This model is a version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) fine-tuned on a dataset of Quick!Draw! sketches (~10% of [QuickDraw's 50M sketches](https://huggingface.co/datasets/kmewhort/quickdraw-bins-50M)).
 It achieves the following results on the evaluation set:
-- Loss: 1.6083
-- Accuracy: 0.7480
+- Loss: 0.7372
+- Accuracy: 0.8098
 
 ## Intended uses & limitations
 
@@ -73,47 +73,29 @@ def binToPIL(packed_drawing):
     return pilImage
 ```
 
-
 ## Training procedure
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 64
+- eval_batch_size: 64
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 128
+- total_train_batch_size: 256
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 20
+- num_epochs: 3
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
-|:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 1.3452        | 1.0   | 3151  | 1.3825          | 0.6702   |
-| 1.052         | 2.0   | 6302  | 1.0776          | 0.7252   |
-| 0.9884        | 3.0   | 9453  | 0.9989          | 0.7443   |
-| 0.8054        | 4.0   | 12604 | 0.9747          | 0.7526   |
-| 0.6271        | 5.0   | 15755 | 0.9770          | 0.7558   |
-| 0.5719        | 6.0   | 18906 | 1.0201          | 0.7528   |
-| 0.3557        | 7.0   | 22057 | 1.0702          | 0.7523   |
-| 0.2637        | 8.0   | 25208 | 1.1324          | 0.7501   |
-| 0.1878        | 9.0   | 28359 | 1.2129          | 0.7434   |
-| 0.1616        | 10.0  | 31510 | 1.2692          | 0.7457   |
-| 0.1148        | 11.0  | 34661 | 1.3425          | 0.7435   |
-| 0.0867        | 12.0  | 37812 | 1.3999          | 0.7430   |
-| 0.065         | 13.0  | 40963 | 1.4472          | 0.7442   |
-| 0.0489        | 14.0  | 44114 | 1.4836          | 0.7457   |
-| 0.0365        | 15.0  | 47265 | 1.5194          | 0.7445   |
-| 0.0386        | 16.0  | 50416 | 1.5506          | 0.7458   |
-| 0.0315        | 17.0  | 53567 | 1.5778          | 0.7461   |
-| 0.0236        | 18.0  | 56718 | 1.5986          | 0.7467   |
-| 0.0264        | 19.0  | 59869 | 1.6085          | 0.7475   |
-| 0.0146        | 20.0  | 63020 | 1.6083          | 0.7480   |
+| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
+|:-------------:|:-----:|:-----:|:--------:|:---------------:|
+| 0.939         | 1.0   | 12606 | 0.7853   | 0.8275          |
+| 0.7312        | 2.0   | 25212 | 0.7587   | 0.8027          |
+| 0.6174        | 3.0   | 37818 | 0.7372   | 0.8098          |
 
 
 ### Framework versions