File size: 2,129 Bytes
395fb22
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b0b7d70
 
395fb22
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-1k-224-finetuned-galaxy10-decals
  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. -->

# convnextv2-tiny-1k-224-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4169
- Accuracy: 0.8673

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.0664        | 0.9978 | 112  | 0.9818          | 0.6725   |
| 0.8019        | 1.9955 | 224  | 0.6333          | 0.7990   |
| 0.6524        | 2.9933 | 336  | 0.5248          | 0.8341   |
| 0.6339        | 4.0    | 449  | 0.4731          | 0.8447   |
| 0.5178        | 4.9978 | 561  | 0.4537          | 0.8503   |
| 0.5907        | 5.9955 | 673  | 0.4556          | 0.8472   |
| 0.5292        | 6.9933 | 785  | 0.4169          | 0.8673   |
| 0.5017        | 8.0    | 898  | 0.4107          | 0.8597   |
| 0.4605        | 8.9978 | 1010 | 0.4062          | 0.8635   |
| 0.4765        | 9.9777 | 1120 | 0.3980          | 0.8647   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1