File size: 2,944 Bytes
c5aa5f3 4dc4ea5 c5aa5f3 4dc4ea5 c5aa5f3 4dc4ea5 c5aa5f3 |
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 |
---
library_name: transformers
license: apache-2.0
base_model: c14kevincardenas/beit-large-patch16-384-limb-person-crop
tags:
- image-sequence-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-beit-limb-seq-t4-2heads-2layers-1e-4lr
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. -->
# finetuned-beit-limb-seq-t4-2heads-2layers-1e-4lr
This model is a fine-tuned version of [c14kevincardenas/beit-large-patch16-384-limb-person-crop](https://huggingface.co/c14kevincardenas/beit-large-patch16-384-limb-person-crop) on the c14kevincardenas/beta_caller_284_person_crop_seq_withlimb_4 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3905
- Accuracy: 0.9198
## 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: 0.0001
- 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: 250
- num_epochs: 20.0
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.05
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.728 | 1.0 | 148 | 0.4692 | 0.8934 |
| 0.4398 | 2.0 | 296 | 0.4154 | 0.9174 |
| 0.4817 | 3.0 | 444 | 0.4183 | 0.9114 |
| 0.4336 | 4.0 | 592 | 0.4365 | 0.9006 |
| 0.4266 | 5.0 | 740 | 0.4001 | 0.9186 |
| 0.4375 | 6.0 | 888 | 0.4102 | 0.9090 |
| 0.3893 | 7.0 | 1036 | 0.4297 | 0.9078 |
| 0.4142 | 8.0 | 1184 | 0.3987 | 0.9222 |
| 0.4409 | 9.0 | 1332 | 0.3905 | 0.9198 |
| 0.3839 | 10.0 | 1480 | 0.3984 | 0.9126 |
| 0.3798 | 11.0 | 1628 | 0.4075 | 0.9138 |
| 0.4059 | 12.0 | 1776 | 0.3997 | 0.9114 |
| 0.3785 | 13.0 | 1924 | 0.4169 | 0.9114 |
| 0.3823 | 14.0 | 2072 | 0.4268 | 0.9102 |
| 0.3601 | 15.0 | 2220 | 0.4115 | 0.9150 |
| 0.3725 | 16.0 | 2368 | 0.3957 | 0.9246 |
| 0.3321 | 17.0 | 2516 | 0.4084 | 0.9138 |
| 0.3718 | 18.0 | 2664 | 0.4134 | 0.9102 |
| 0.3605 | 19.0 | 2812 | 0.4041 | 0.9150 |
| 0.3167 | 20.0 | 2960 | 0.4074 | 0.9186 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
|