Model save

README.md

@@ -1,9 +1,6 @@
 ---
-license: apache-2.0
-base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
+base_model: microsoft/dit-base-finetuned-rvlcdip
 tags:
-- image-classification
-- vision
 - generated_from_trainer
 metrics:
 - f1
@@ -17,9 +14,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 # donut-base-beans
 
-This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
+This model is a fine-tuned version of [microsoft/dit-base-finetuned-rvlcdip](https://huggingface.co/microsoft/dit-base-finetuned-rvlcdip) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0517
+- Loss: 0.0413
 - F1: 0.3303
 
 ## Model description
@@ -40,8 +37,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 3e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 64
+- eval_batch_size: 64
 - seed: 1337
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -49,13 +46,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | F1  | Validation Loss |
-|:-------------:|:-----:|:-----:|:---:|:---------------:|
-| 0.0672        | 1.0   | 13466 | 0.0 | 0.0696          |
-| 0.0612        | 2.0   | 26932 | 0.0 | 0.0588          |
-| 0.0496        | 3.0   | 40398 | 0.0 | 0.0556          |
-| 0.0443        | 4.0   | 53864 | 0.0 | 0.0535          |
-| 0.0683        | 5.0   | 67330 | 0.0 | 0.0517          |
+| Training Loss | Epoch | Step  | Validation Loss | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 0.0584        | 1.0   | 3367  | 0.0530          | 0.3303 |
+| 0.0679        | 2.0   | 6734  | 0.0460          | 0.3303 |
+| 0.0508        | 3.0   | 10101 | 0.0452          | 0.3303 |
+| 0.0539        | 4.0   | 13468 | 0.0435          | 0.3303 |
+| 0.0568        | 5.0   | 16835 | 0.0413          | 0.3303 |
 
 
 ### Framework versions