LaLegumbreArtificial commited on
Commit
ae8d58e
1 Parent(s): 5e12643

End of training

Browse files
Files changed (1) hide show
  1. README.md +70 -0
README.md ADDED
@@ -0,0 +1,70 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: google/vit-base-patch16-224
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - accuracy
8
+ model-index:
9
+ - name: Model_custom_pythorch
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jose-contreras-itj/huggingface/runs/ma9pv9di)
17
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jose-contreras-itj/huggingface/runs/ma9pv9di)
18
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/jose-contreras-itj/huggingface/runs/ma9pv9di)
19
+ # Model_custom_pythorch
20
+
21
+ This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
22
+ It achieves the following results on the evaluation set:
23
+ - Loss: 0.0250
24
+ - Accuracy: 0.991
25
+
26
+ ## Model description
27
+
28
+ More information needed
29
+
30
+ ## Intended uses & limitations
31
+
32
+ More information needed
33
+
34
+ ## Training and evaluation data
35
+
36
+ More information needed
37
+
38
+ ## Training procedure
39
+
40
+ ### Training hyperparameters
41
+
42
+ The following hyperparameters were used during training:
43
+ - learning_rate: 5e-05
44
+ - train_batch_size: 32
45
+ - eval_batch_size: 32
46
+ - seed: 42
47
+ - gradient_accumulation_steps: 4
48
+ - total_train_batch_size: 128
49
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
+ - lr_scheduler_type: linear
51
+ - lr_scheduler_warmup_ratio: 0.1
52
+ - num_epochs: 5
53
+
54
+ ### Training results
55
+
56
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
57
+ |:-------------:|:------:|:----:|:---------------:|:--------:|
58
+ | 0.0682 | 0.9954 | 109 | 0.0756 | 0.9733 |
59
+ | 0.0522 | 2.0 | 219 | 0.0444 | 0.9837 |
60
+ | 0.0358 | 2.9954 | 328 | 0.0361 | 0.9872 |
61
+ | 0.0222 | 4.0 | 438 | 0.0386 | 0.9863 |
62
+ | 0.0163 | 4.9772 | 545 | 0.0250 | 0.991 |
63
+
64
+
65
+ ### Framework versions
66
+
67
+ - Transformers 4.42.3
68
+ - Pytorch 2.1.2
69
+ - Datasets 2.20.0
70
+ - Tokenizers 0.19.1