File size: 4,440 Bytes
d3ed16e 963c482 d3ed16e 963c482 d3ed16e 963c482 d3ed16e |
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 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 |
---
license: apache-2.0
base_model: facebook/convnextv2-nano-1k-224
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: convnextv2-nano-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-nano-1k-224-finetuned-galaxy10-decals
This model is a fine-tuned version of [facebook/convnextv2-nano-1k-224](https://huggingface.co/facebook/convnextv2-nano-1k-224) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7023
- Accuracy: 0.8591
- Precision: 0.8565
- Recall: 0.8591
- F1: 0.8566
## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0509 | 0.99 | 62 | 0.9876 | 0.6561 | 0.6692 | 0.6561 | 0.6355 |
| 0.8315 | 2.0 | 125 | 0.6745 | 0.7638 | 0.7726 | 0.7638 | 0.7581 |
| 0.7659 | 2.99 | 187 | 0.6651 | 0.7897 | 0.8092 | 0.7897 | 0.7858 |
| 0.6645 | 4.0 | 250 | 0.6068 | 0.8027 | 0.8117 | 0.8027 | 0.8031 |
| 0.6212 | 4.99 | 312 | 0.5895 | 0.8061 | 0.8158 | 0.8061 | 0.8058 |
| 0.624 | 6.0 | 375 | 0.5128 | 0.8269 | 0.8223 | 0.8269 | 0.8220 |
| 0.5648 | 6.99 | 437 | 0.5219 | 0.8196 | 0.8239 | 0.8196 | 0.8171 |
| 0.5235 | 8.0 | 500 | 0.5652 | 0.8275 | 0.8303 | 0.8275 | 0.8270 |
| 0.5316 | 8.99 | 562 | 0.4804 | 0.8427 | 0.8431 | 0.8427 | 0.8396 |
| 0.4756 | 10.0 | 625 | 0.5345 | 0.8213 | 0.8188 | 0.8213 | 0.8169 |
| 0.4758 | 10.99 | 687 | 0.5560 | 0.8326 | 0.8324 | 0.8326 | 0.8302 |
| 0.4499 | 12.0 | 750 | 0.5283 | 0.8416 | 0.8458 | 0.8416 | 0.8423 |
| 0.4274 | 12.99 | 812 | 0.5347 | 0.8348 | 0.8364 | 0.8348 | 0.8337 |
| 0.4148 | 14.0 | 875 | 0.5326 | 0.8422 | 0.8396 | 0.8422 | 0.8383 |
| 0.3822 | 14.99 | 937 | 0.5116 | 0.8410 | 0.8442 | 0.8410 | 0.8412 |
| 0.3613 | 16.0 | 1000 | 0.6081 | 0.8230 | 0.8245 | 0.8230 | 0.8210 |
| 0.2903 | 16.99 | 1062 | 0.6212 | 0.8298 | 0.8289 | 0.8298 | 0.8275 |
| 0.3405 | 18.0 | 1125 | 0.6093 | 0.8377 | 0.8394 | 0.8377 | 0.8368 |
| 0.2999 | 18.99 | 1187 | 0.6482 | 0.8393 | 0.8352 | 0.8393 | 0.8356 |
| 0.2792 | 20.0 | 1250 | 0.6473 | 0.8484 | 0.8482 | 0.8484 | 0.8419 |
| 0.2681 | 20.99 | 1312 | 0.6710 | 0.8467 | 0.8428 | 0.8467 | 0.8425 |
| 0.2966 | 22.0 | 1375 | 0.6355 | 0.8534 | 0.8513 | 0.8534 | 0.8514 |
| 0.2609 | 22.99 | 1437 | 0.6850 | 0.8399 | 0.8406 | 0.8399 | 0.8397 |
| 0.2281 | 24.0 | 1500 | 0.7124 | 0.8444 | 0.8444 | 0.8444 | 0.8440 |
| 0.2354 | 24.99 | 1562 | 0.7317 | 0.8427 | 0.8394 | 0.8427 | 0.8395 |
| 0.2188 | 26.0 | 1625 | 0.6753 | 0.8512 | 0.8490 | 0.8512 | 0.8489 |
| 0.2118 | 26.99 | 1687 | 0.6865 | 0.8506 | 0.8495 | 0.8506 | 0.8494 |
| 0.2232 | 28.0 | 1750 | 0.7098 | 0.8557 | 0.8531 | 0.8557 | 0.8535 |
| 0.2104 | 28.99 | 1812 | 0.7023 | 0.8591 | 0.8565 | 0.8591 | 0.8566 |
| 0.1936 | 29.76 | 1860 | 0.7043 | 0.8557 | 0.8540 | 0.8557 | 0.8541 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1
|