File size: 2,219 Bytes
89d1138 e11c714 89d1138 e11c714 89d1138 e11c714 89d1138 |
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 |
---
license: apache-2.0
base_model: microsoft/beit-large-patch16-384
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: beit-large-patch16-384-limb-person-crop-8_1e-5_5e-3_0.1
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. -->
# beit-large-patch16-384-limb-person-crop-8_1e-5_5e-3_0.1
This model is a fine-tuned version of [microsoft/beit-large-patch16-384](https://huggingface.co/microsoft/beit-large-patch16-384) on the c14kevincardenas/beta_caller_284_person_crop dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8764
- Accuracy: 0.7181
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2014
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4023 | 1.0 | 214 | 1.3975 | 0.2745 |
| 1.2554 | 2.0 | 428 | 1.1980 | 0.4900 |
| 1.1635 | 3.0 | 642 | 1.0272 | 0.5970 |
| 1.099 | 4.0 | 856 | 1.0476 | 0.5954 |
| 1.067 | 5.0 | 1070 | 0.9586 | 0.6600 |
| 1.0153 | 6.0 | 1284 | 0.9101 | 0.6816 |
| 0.9507 | 7.0 | 1498 | 0.9307 | 0.6833 |
| 0.9487 | 8.0 | 1712 | 0.8812 | 0.7148 |
| 0.9365 | 9.0 | 1926 | 0.8764 | 0.7181 |
| 0.9186 | 10.0 | 2140 | 0.8818 | 0.7090 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
|