End of training

README.md

@@ -0,0 +1,125 @@
+---
+license: apache-2.0
+base_model: facebook/deit-small-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: smids_5x_deit_small_rms_001_fold2
+  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: 0.757071547420965
+---
+
+<!-- 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_5x_deit_small_rms_001_fold2
+
+This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5587
+- Accuracy: 0.7571
+
+## 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: 0.001
+- 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.1114        | 1.0   | 375   | 1.0890          | 0.3910   |
+| 0.8594        | 2.0   | 750   | 0.8338          | 0.5258   |
+| 0.7942        | 3.0   | 1125  | 0.8187          | 0.5857   |
+| 0.8295        | 4.0   | 1500  | 0.8518          | 0.5441   |
+| 0.7679        | 5.0   | 1875  | 0.8037          | 0.5574   |
+| 0.78          | 6.0   | 2250  | 0.8086          | 0.5641   |
+| 0.8051        | 7.0   | 2625  | 0.8475          | 0.5707   |
+| 0.7931        | 8.0   | 3000  | 0.7986          | 0.5740   |
+| 0.787         | 9.0   | 3375  | 0.8111          | 0.6273   |
+| 0.7865        | 10.0  | 3750  | 0.7854          | 0.5874   |
+| 0.7545        | 11.0  | 4125  | 0.7499          | 0.6156   |
+| 0.8266        | 12.0  | 4500  | 0.7256          | 0.6373   |
+| 0.699         | 13.0  | 4875  | 0.7372          | 0.6456   |
+| 0.7725        | 14.0  | 5250  | 0.7195          | 0.6439   |
+| 0.7834        | 15.0  | 5625  | 0.7235          | 0.6489   |
+| 0.6954        | 16.0  | 6000  | 0.7061          | 0.6589   |
+| 0.6911        | 17.0  | 6375  | 0.8229          | 0.5973   |
+| 0.667         | 18.0  | 6750  | 0.6746          | 0.6772   |
+| 0.6889        | 19.0  | 7125  | 0.6831          | 0.6955   |
+| 0.6628        | 20.0  | 7500  | 0.6921          | 0.6922   |
+| 0.7228        | 21.0  | 7875  | 0.6764          | 0.6656   |
+| 0.7022        | 22.0  | 8250  | 0.6797          | 0.6905   |
+| 0.6549        | 23.0  | 8625  | 0.6709          | 0.6772   |
+| 0.7183        | 24.0  | 9000  | 0.6429          | 0.6955   |
+| 0.6612        | 25.0  | 9375  | 0.6503          | 0.6988   |
+| 0.6901        | 26.0  | 9750  | 0.7018          | 0.6739   |
+| 0.7038        | 27.0  | 10125 | 0.6168          | 0.7271   |
+| 0.6364        | 28.0  | 10500 | 0.6219          | 0.7121   |
+| 0.6477        | 29.0  | 10875 | 0.6546          | 0.7188   |
+| 0.5753        | 30.0  | 11250 | 0.6252          | 0.7221   |
+| 0.6932        | 31.0  | 11625 | 0.6174          | 0.7271   |
+| 0.6245        | 32.0  | 12000 | 0.6281          | 0.7255   |
+| 0.6083        | 33.0  | 12375 | 0.6211          | 0.7105   |
+| 0.6277        | 34.0  | 12750 | 0.5911          | 0.7471   |
+| 0.596         | 35.0  | 13125 | 0.5943          | 0.7304   |
+| 0.5539        | 36.0  | 13500 | 0.5798          | 0.7121   |
+| 0.6231        | 37.0  | 13875 | 0.5842          | 0.7321   |
+| 0.5692        | 38.0  | 14250 | 0.5897          | 0.7288   |
+| 0.5587        | 39.0  | 14625 | 0.6220          | 0.7155   |
+| 0.5891        | 40.0  | 15000 | 0.6063          | 0.7338   |
+| 0.561         | 41.0  | 15375 | 0.5930          | 0.7338   |
+| 0.5901        | 42.0  | 15750 | 0.5990          | 0.7288   |
+| 0.5194        | 43.0  | 16125 | 0.5632          | 0.7488   |
+| 0.5311        | 44.0  | 16500 | 0.5715          | 0.7488   |
+| 0.5414        | 45.0  | 16875 | 0.5640          | 0.7537   |
+| 0.5291        | 46.0  | 17250 | 0.5674          | 0.7504   |
+| 0.5724        | 47.0  | 17625 | 0.5765          | 0.7454   |
+| 0.4849        | 48.0  | 18000 | 0.5625          | 0.7438   |
+| 0.5463        | 49.0  | 18375 | 0.5558          | 0.7571   |
+| 0.4844        | 50.0  | 18750 | 0.5587          | 0.7571   |
+
+
+### 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 sha256:7dbd82c19ebaa35e9f174abc38e507239558bc7ce21654ee09ca9295bcf59059
+oid sha256:66ce7a27f9d733de44f51969edd896ec55de23923eccd52762d23cc88a600bb3
 size 86735658