End of training

README.md

@@ -1,68 +1,78 @@
----
-license: apache-2.0
-tags:
-- generated_from_trainer
-base_model: google/vit-base-patch16-224-in21k
-metrics:
-- accuracy
-model-index:
-- name: vit-xray-pneumonia-classification
-  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. -->
-
-# vit-xray-pneumonia-classification
-
-This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1602
-- Accuracy: 0.9313
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 64
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 15
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:--------:|
-| 0.4638        | 0.9882 | 63   | 0.2024          | 0.9236   |
-| 0.1987        | 1.9922 | 127  | 0.1342          | 0.9588   |
-| 0.1637        | 2.9961 | 191  | 0.1534          | 0.9442   |
-| 0.16          | 4.0    | 255  | 0.1365          | 0.9485   |
-| 0.1344        | 4.9882 | 318  | 0.1602          | 0.9313   |
-
-
-### Framework versions
-
-- Transformers 4.40.1
-- Pytorch 2.2.1+cu121
-- Datasets 2.19.0
-- Tokenizers 0.19.1
+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vit-xray-pneumonia-classification
+  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. -->
+
+# vit-xray-pneumonia-classification
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0740
+- Accuracy: 0.9734
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|
+| 0.4843        | 0.9882  | 63   | 0.1954          | 0.9408   |
+| 0.1986        | 1.9922  | 127  | 0.1483          | 0.9494   |
+| 0.1694        | 2.9961  | 191  | 0.1316          | 0.9459   |
+| 0.1368        | 4.0     | 255  | 0.1207          | 0.9554   |
+| 0.1399        | 4.9882  | 318  | 0.1738          | 0.9296   |
+| 0.1203        | 5.9922  | 382  | 0.0966          | 0.9631   |
+| 0.1085        | 6.9961  | 446  | 0.0956          | 0.9631   |
+| 0.1046        | 8.0     | 510  | 0.0952          | 0.9665   |
+| 0.0883        | 8.9882  | 573  | 0.0990          | 0.9665   |
+| 0.0773        | 9.9922  | 637  | 0.0896          | 0.9717   |
+| 0.0815        | 10.9961 | 701  | 0.1084          | 0.9605   |
+| 0.0793        | 12.0    | 765  | 0.0767          | 0.9742   |
+| 0.0778        | 12.9882 | 828  | 0.0885          | 0.9691   |
+| 0.0609        | 13.9922 | 892  | 0.0778          | 0.9708   |
+| 0.0685        | 14.8235 | 945  | 0.0740          | 0.9734   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.3.0
+- Datasets 2.19.0
+- Tokenizers 0.19.1