End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/dinov2-base-imagenet1k-1-layer
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Foot
+  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. -->
+
+# Foot
+
+This model is a fine-tuned version of [facebook/dinov2-base-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-base-imagenet1k-1-layer) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0747
+- Accuracy: 0.4865
+
+## 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: 10
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 20
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 2    | 1.2201          | 0.3378   |
+| No log        | 2.0   | 4    | 1.2243          | 0.2568   |
+| No log        | 3.0   | 6    | 1.2672          | 0.2703   |
+| No log        | 4.0   | 8    | 1.2501          | 0.2297   |
+| 1.2006        | 5.0   | 10   | 1.1975          | 0.2973   |
+| 1.2006        | 6.0   | 12   | 1.1270          | 0.3919   |
+| 1.2006        | 7.0   | 14   | 1.0999          | 0.3243   |
+| 1.2006        | 8.0   | 16   | 1.1497          | 0.3649   |
+| 1.2006        | 9.0   | 18   | 1.1006          | 0.3108   |
+| 1.1058        | 10.0  | 20   | 1.1271          | 0.3514   |
+| 1.1058        | 11.0  | 22   | 1.1273          | 0.3784   |
+| 1.1058        | 12.0  | 24   | 1.1639          | 0.2838   |
+| 1.1058        | 13.0  | 26   | 1.1421          | 0.4054   |
+| 1.1058        | 14.0  | 28   | 1.1190          | 0.3514   |
+| 1.0489        | 15.0  | 30   | 1.1735          | 0.3243   |
+| 1.0489        | 16.0  | 32   | 1.1422          | 0.3378   |
+| 1.0489        | 17.0  | 34   | 1.1414          | 0.3649   |
+| 1.0489        | 18.0  | 36   | 1.1033          | 0.4189   |
+| 1.0489        | 19.0  | 38   | 1.0747          | 0.3919   |
+| 0.9717        | 20.0  | 40   | 1.0952          | 0.3919   |
+| 0.9717        | 21.0  | 42   | 1.1063          | 0.3784   |
+| 0.9717        | 22.0  | 44   | 1.0822          | 0.3649   |
+| 0.9717        | 23.0  | 46   | 1.0768          | 0.3784   |
+| 0.9717        | 24.0  | 48   | 1.0753          | 0.4595   |
+| 0.9816        | 25.0  | 50   | 1.0531          | 0.4054   |
+| 0.9816        | 26.0  | 52   | 1.0624          | 0.4189   |
+| 0.9816        | 27.0  | 54   | 1.0690          | 0.4459   |
+| 0.9816        | 28.0  | 56   | 1.1392          | 0.3514   |
+| 0.9816        | 29.0  | 58   | 1.0696          | 0.4054   |
+| 0.9576        | 30.0  | 60   | 1.0747          | 0.4865   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0