End of training

README.md

@@ -0,0 +1,125 @@
+---
+license: apache-2.0
+base_model: facebook/deit-base-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: smids_3x_deit_base_sgd_00001_fold3
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: test
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.4266666666666667
+---
+
+<!-- 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. -->
+
+# smids_3x_deit_base_sgd_00001_fold3
+
+This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0784
+- Accuracy: 0.4267
+
+## 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: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.1104        | 1.0   | 225   | 1.1064          | 0.345    |
+| 1.1269        | 2.0   | 450   | 1.1051          | 0.355    |
+| 1.1082        | 3.0   | 675   | 1.1039          | 0.3667   |
+| 1.0954        | 4.0   | 900   | 1.1026          | 0.365    |
+| 1.1069        | 5.0   | 1125  | 1.1015          | 0.36     |
+| 1.1012        | 6.0   | 1350  | 1.1003          | 0.3667   |
+| 1.1071        | 7.0   | 1575  | 1.0992          | 0.3733   |
+| 1.1242        | 8.0   | 1800  | 1.0982          | 0.3767   |
+| 1.086         | 9.0   | 2025  | 1.0971          | 0.3783   |
+| 1.0866        | 10.0  | 2250  | 1.0961          | 0.3867   |
+| 1.0948        | 11.0  | 2475  | 1.0952          | 0.3833   |
+| 1.0863        | 12.0  | 2700  | 1.0942          | 0.385    |
+| 1.0844        | 13.0  | 2925  | 1.0933          | 0.3833   |
+| 1.0933        | 14.0  | 3150  | 1.0925          | 0.3867   |
+| 1.0947        | 15.0  | 3375  | 1.0916          | 0.3917   |
+| 1.084         | 16.0  | 3600  | 1.0908          | 0.39     |
+| 1.0986        | 17.0  | 3825  | 1.0900          | 0.395    |
+| 1.0824        | 18.0  | 4050  | 1.0893          | 0.3967   |
+| 1.0832        | 19.0  | 4275  | 1.0886          | 0.395    |
+| 1.0894        | 20.0  | 4500  | 1.0879          | 0.3967   |
+| 1.0841        | 21.0  | 4725  | 1.0872          | 0.4      |
+| 1.0872        | 22.0  | 4950  | 1.0865          | 0.405    |
+| 1.0916        | 23.0  | 5175  | 1.0859          | 0.4117   |
+| 1.0847        | 24.0  | 5400  | 1.0853          | 0.4117   |
+| 1.0901        | 25.0  | 5625  | 1.0848          | 0.41     |
+| 1.0732        | 26.0  | 5850  | 1.0842          | 0.41     |
+| 1.0848        | 27.0  | 6075  | 1.0837          | 0.4133   |
+| 1.0818        | 28.0  | 6300  | 1.0832          | 0.415    |
+| 1.0774        | 29.0  | 6525  | 1.0828          | 0.415    |
+| 1.0812        | 30.0  | 6750  | 1.0823          | 0.4183   |
+| 1.0886        | 31.0  | 6975  | 1.0819          | 0.4183   |
+| 1.0712        | 32.0  | 7200  | 1.0815          | 0.42     |
+| 1.0744        | 33.0  | 7425  | 1.0812          | 0.42     |
+| 1.0756        | 34.0  | 7650  | 1.0808          | 0.425    |
+| 1.0664        | 35.0  | 7875  | 1.0805          | 0.4267   |
+| 1.0977        | 36.0  | 8100  | 1.0802          | 0.4283   |
+| 1.0683        | 37.0  | 8325  | 1.0799          | 0.4283   |
+| 1.0735        | 38.0  | 8550  | 1.0797          | 0.4267   |
+| 1.0832        | 39.0  | 8775  | 1.0795          | 0.4267   |
+| 1.0815        | 40.0  | 9000  | 1.0793          | 0.4267   |
+| 1.0823        | 41.0  | 9225  | 1.0791          | 0.425    |
+| 1.0956        | 42.0  | 9450  | 1.0789          | 0.425    |
+| 1.0851        | 43.0  | 9675  | 1.0788          | 0.425    |
+| 1.0774        | 44.0  | 9900  | 1.0787          | 0.4267   |
+| 1.0466        | 45.0  | 10125 | 1.0786          | 0.4267   |
+| 1.0871        | 46.0  | 10350 | 1.0785          | 0.4267   |
+| 1.0722        | 47.0  | 10575 | 1.0784          | 0.4267   |
+| 1.069         | 48.0  | 10800 | 1.0784          | 0.4267   |
+| 1.0654        | 49.0  | 11025 | 1.0784          | 0.4267   |
+| 1.0659        | 50.0  | 11250 | 1.0784          | 0.4267   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.12.0
+- Tokenizers 0.13.2

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:97c1d1342f296278e0367def81218eeb1becba8a275daeb7ef937600855cf98a
+oid sha256:baac65ef978d6b9b89956cbd5ee8c42327350f0687cf0804022abc45f19c726b
 size 343272234