File size: 2,659 Bytes
b6a92c1 fe77a92 b6a92c1 fe77a92 b6a92c1 fe77a92 b6a92c1 855fc23 b6a92c1 855fc23 b6a92c1 |
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 |
---
library_name: transformers
license: apache-2.0
base_model: facebook/detr-resnet-50
tags:
- image-regression
- human-movement
- vision
- generated_from_trainer
model-index:
- name: target_hold
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. -->
# target_hold
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on the c14kevincardenas/beta_caller_284_target_hold dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8720
- Iou: 0.0008
## 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: 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Iou |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.2348 | 1.0 | 100 | 1.1666 | 0.0001 |
| 1.0043 | 2.0 | 200 | 0.9816 | 0.0023 |
| 0.9101 | 3.0 | 300 | 0.9058 | 0.0020 |
| 0.8846 | 4.0 | 400 | 0.8883 | 0.0013 |
| 0.8755 | 5.0 | 500 | 0.8819 | 0.0011 |
| 0.8714 | 6.0 | 600 | 0.8789 | 0.0010 |
| 0.8684 | 7.0 | 700 | 0.8773 | 0.0009 |
| 0.8664 | 8.0 | 800 | 0.8764 | 0.0008 |
| 0.8677 | 9.0 | 900 | 0.8752 | 0.0009 |
| 0.863 | 10.0 | 1000 | 0.8747 | 0.0009 |
| 0.8619 | 11.0 | 1100 | 0.8737 | 0.0009 |
| 0.8637 | 12.0 | 1200 | 0.8732 | 0.0009 |
| 0.8632 | 13.0 | 1300 | 0.8730 | 0.0009 |
| 0.8581 | 14.0 | 1400 | 0.8727 | 0.0009 |
| 0.8615 | 15.0 | 1500 | 0.8724 | 0.0009 |
| 0.8604 | 16.0 | 1600 | 0.8724 | 0.0008 |
| 0.8606 | 17.0 | 1700 | 0.8720 | 0.0009 |
| 0.8592 | 18.0 | 1800 | 0.8720 | 0.0009 |
| 0.8621 | 19.0 | 1900 | 0.8720 | 0.0008 |
| 0.8629 | 20.0 | 2000 | 0.8720 | 0.0008 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1
|