End of training

README.md

@@ -4,8 +4,8 @@ license: apache-2.0
 base_model: google/vit-base-patch16-224-in21k
 tags:
 - generated_from_trainer
-datasets:
-- imagefolder
+metrics:
+- accuracy
 model-index:
 - name: image_classification
   results: []
@@ -16,15 +16,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # image_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 the imagefolder dataset.
+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:
-- eval_loss: 2.0879
-- eval_model_preparation_time: 0.0065
-- eval_accuracy: 0.1187
-- eval_runtime: 43.6598
-- eval_samples_per_second: 3.665
-- eval_steps_per_second: 0.115
-- step: 0
+- Loss: 1.6535
+- Accuracy: 0.878
 
 ## Model description
 
@@ -43,20 +38,29 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0001
-- train_batch_size: 32
-- eval_batch_size: 32
+- learning_rate: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
-- gradient_accumulation_steps: 2
+- gradient_accumulation_steps: 4
 - total_train_batch_size: 64
-- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_ratio: 0.3
-- num_epochs: 20
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.7065        | 1.0   | 63   | 2.5465          | 0.799    |
+| 1.8582        | 2.0   | 126  | 1.8365          | 0.848    |
+| 1.6103        | 2.96  | 186  | 1.6695          | 0.863    |
+
 
 ### Framework versions
 
-- Transformers 4.46.2
-- Pytorch 2.5.1+cu121
-- Datasets 3.1.0
-- Tokenizers 0.20.3
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.6.0
+- Tokenizers 0.21.1

runs/May15_15-52-39_eb3fec5dd0b0/events.out.tfevents.1747325096.eb3fec5dd0b0.7448.1

@@ -0,0 +1,3 @@
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+oid sha256:59cce5ab4c7f4637df43ca57dc0523329974dda2b0cc1058e0c6a7badc9cf052
+size 411