File size: 10,042 Bytes
0877fe8 |
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 99 100 101 102 103 104 105 |
---
license: apache-2.0
base_model: microsoft/conditional-detr-resnet-50
tags:
- generated_from_trainer
datasets:
- dsi
model-index:
- name: detr_finetunned_air
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. -->
# detr_finetunned_air
This model is a fine-tuned version of [microsoft/conditional-detr-resnet-50](https://huggingface.co/microsoft/conditional-detr-resnet-50) on the dsi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8865
- Map: 0.32
- Map 50: 0.778
- Map 75: 0.1885
- Map Small: 0.3219
- Map Medium: 0.0139
- Map Large: -1.0
- Mar 1: 0.0252
- Mar 10: 0.1994
- Mar 100: 0.487
- Mar Small: 0.4896
- Mar Medium: 0.0122
- Mar Large: -1.0
- Map Falciparum Trophozoite: 0.32
- Mar 100 Falciparum Trophozoite: 0.487
- Map Wbc: -1.0
- Mar 100 Wbc: -1.0
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Map | Map 50 | Map 75 | Map Small | Map Medium | Map Large | Mar 1 | Mar 10 | Mar 100 | Mar Small | Mar Medium | Mar Large | Map Falciparum Trophozoite | Mar 100 Falciparum Trophozoite | Map Wbc | Mar 100 Wbc |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------:|:---------:|:------:|:------:|:-------:|:---------:|:----------:|:---------:|:--------------------------:|:------------------------------:|:-------:|:-----------:|
| No log | 1.0 | 209 | 1.2045 | 0.1719 | 0.4768 | 0.0896 | 0.1728 | 0.0167 | -1.0 | 0.0188 | 0.139 | 0.4221 | 0.4242 | 0.0184 | -1.0 | 0.1719 | 0.4221 | -1.0 | -1.0 |
| No log | 2.0 | 418 | 1.1177 | 0.2155 | 0.5922 | 0.1044 | 0.2165 | 0.005 | -1.0 | 0.021 | 0.1601 | 0.4249 | 0.4272 | 0.0041 | -1.0 | 0.2155 | 0.4249 | -1.0 | -1.0 |
| 1.339 | 3.0 | 627 | 1.0571 | 0.249 | 0.6576 | 0.1328 | 0.2503 | 0.0229 | -1.0 | 0.0236 | 0.1739 | 0.44 | 0.4422 | 0.0224 | -1.0 | 0.249 | 0.44 | -1.0 | -1.0 |
| 1.339 | 4.0 | 836 | 1.0675 | 0.2358 | 0.6473 | 0.1175 | 0.2369 | 0.0139 | -1.0 | 0.0216 | 0.166 | 0.4242 | 0.4265 | 0.0122 | -1.0 | 0.2358 | 0.4242 | -1.0 | -1.0 |
| 1.0423 | 5.0 | 1045 | 1.0266 | 0.2509 | 0.6759 | 0.1224 | 0.2525 | 0.0 | -1.0 | 0.0228 | 0.1711 | 0.4318 | 0.4341 | 0.0 | -1.0 | 0.2509 | 0.4318 | -1.0 | -1.0 |
| 1.0423 | 6.0 | 1254 | 1.0054 | 0.2569 | 0.6847 | 0.1269 | 0.2579 | 0.0091 | -1.0 | 0.0226 | 0.1754 | 0.4467 | 0.4491 | 0.0122 | -1.0 | 0.2569 | 0.4467 | -1.0 | -1.0 |
| 1.0423 | 7.0 | 1463 | 0.9812 | 0.2767 | 0.7163 | 0.1454 | 0.2782 | 0.0114 | -1.0 | 0.0238 | 0.1831 | 0.4539 | 0.4562 | 0.0224 | -1.0 | 0.2767 | 0.4539 | -1.0 | -1.0 |
| 0.99 | 8.0 | 1672 | 1.0019 | 0.271 | 0.7169 | 0.1358 | 0.2724 | 0.0096 | -1.0 | 0.0236 | 0.1801 | 0.4515 | 0.4538 | 0.0143 | -1.0 | 0.271 | 0.4515 | -1.0 | -1.0 |
| 0.99 | 9.0 | 1881 | 0.9623 | 0.2873 | 0.731 | 0.1597 | 0.2886 | 0.0064 | -1.0 | 0.0251 | 0.1865 | 0.4608 | 0.4633 | 0.0061 | -1.0 | 0.2873 | 0.4608 | -1.0 | -1.0 |
| 0.9521 | 10.0 | 2090 | 0.9763 | 0.273 | 0.711 | 0.1419 | 0.2742 | 0.011 | -1.0 | 0.0229 | 0.178 | 0.4482 | 0.4506 | 0.0122 | -1.0 | 0.273 | 0.4482 | -1.0 | -1.0 |
| 0.9521 | 11.0 | 2299 | 0.9551 | 0.2906 | 0.7354 | 0.1634 | 0.2925 | 0.0064 | -1.0 | 0.0248 | 0.188 | 0.4654 | 0.4679 | 0.0082 | -1.0 | 0.2906 | 0.4654 | -1.0 | -1.0 |
| 0.92 | 12.0 | 2508 | 0.9430 | 0.2956 | 0.7454 | 0.1685 | 0.297 | 0.0052 | -1.0 | 0.0248 | 0.1886 | 0.4696 | 0.4721 | 0.0061 | -1.0 | 0.2956 | 0.4696 | -1.0 | -1.0 |
| 0.92 | 13.0 | 2717 | 0.9434 | 0.2953 | 0.7445 | 0.1721 | 0.2968 | 0.0233 | -1.0 | 0.0245 | 0.1895 | 0.4673 | 0.4697 | 0.0265 | -1.0 | 0.2953 | 0.4673 | -1.0 | -1.0 |
| 0.92 | 14.0 | 2926 | 0.9228 | 0.3001 | 0.7498 | 0.1716 | 0.3015 | 0.0132 | -1.0 | 0.0244 | 0.1899 | 0.4767 | 0.4792 | 0.0143 | -1.0 | 0.3001 | 0.4767 | -1.0 | -1.0 |
| 0.8986 | 15.0 | 3135 | 0.9194 | 0.3036 | 0.7566 | 0.1757 | 0.3055 | 0.0119 | -1.0 | 0.0243 | 0.1929 | 0.4778 | 0.4803 | 0.0143 | -1.0 | 0.3036 | 0.4778 | -1.0 | -1.0 |
| 0.8986 | 16.0 | 3344 | 0.9166 | 0.3063 | 0.7558 | 0.1791 | 0.3081 | 0.0129 | -1.0 | 0.0253 | 0.1928 | 0.4762 | 0.4787 | 0.0122 | -1.0 | 0.3063 | 0.4762 | -1.0 | -1.0 |
| 0.875 | 17.0 | 3553 | 0.9218 | 0.3021 | 0.7573 | 0.1653 | 0.3041 | 0.0089 | -1.0 | 0.0251 | 0.1908 | 0.4721 | 0.4746 | 0.0082 | -1.0 | 0.3021 | 0.4721 | -1.0 | -1.0 |
| 0.875 | 18.0 | 3762 | 0.9094 | 0.3032 | 0.7548 | 0.1705 | 0.3052 | 0.0079 | -1.0 | 0.0242 | 0.1921 | 0.4769 | 0.4795 | 0.0061 | -1.0 | 0.3032 | 0.4769 | -1.0 | -1.0 |
| 0.875 | 19.0 | 3971 | 0.8965 | 0.3156 | 0.7713 | 0.1873 | 0.3171 | 0.0187 | -1.0 | 0.0247 | 0.1963 | 0.484 | 0.4865 | 0.0184 | -1.0 | 0.3156 | 0.484 | -1.0 | -1.0 |
| 0.8575 | 20.0 | 4180 | 0.8995 | 0.3101 | 0.7674 | 0.1854 | 0.3116 | 0.0069 | -1.0 | 0.0247 | 0.1964 | 0.4803 | 0.4829 | 0.0061 | -1.0 | 0.3101 | 0.4803 | -1.0 | -1.0 |
| 0.8575 | 21.0 | 4389 | 0.8992 | 0.3118 | 0.7676 | 0.1852 | 0.3131 | 0.0119 | -1.0 | 0.0252 | 0.1954 | 0.4794 | 0.4819 | 0.0102 | -1.0 | 0.3118 | 0.4794 | -1.0 | -1.0 |
| 0.834 | 22.0 | 4598 | 0.8912 | 0.3169 | 0.7744 | 0.1894 | 0.3186 | 0.0089 | -1.0 | 0.0254 | 0.1977 | 0.4876 | 0.4902 | 0.0082 | -1.0 | 0.3169 | 0.4876 | -1.0 | -1.0 |
| 0.834 | 23.0 | 4807 | 0.8922 | 0.3175 | 0.7761 | 0.1895 | 0.3195 | 0.0083 | -1.0 | 0.0255 | 0.1984 | 0.4881 | 0.4907 | 0.0102 | -1.0 | 0.3175 | 0.4881 | -1.0 | -1.0 |
| 0.8217 | 24.0 | 5016 | 0.8946 | 0.3153 | 0.7735 | 0.1809 | 0.3167 | 0.0119 | -1.0 | 0.0249 | 0.1972 | 0.4819 | 0.4844 | 0.0102 | -1.0 | 0.3153 | 0.4819 | -1.0 | -1.0 |
| 0.8217 | 25.0 | 5225 | 0.8891 | 0.3198 | 0.7801 | 0.1877 | 0.3213 | 0.0089 | -1.0 | 0.025 | 0.1981 | 0.4878 | 0.4903 | 0.0082 | -1.0 | 0.3198 | 0.4878 | -1.0 | -1.0 |
| 0.8217 | 26.0 | 5434 | 0.8867 | 0.3206 | 0.7794 | 0.1894 | 0.3223 | 0.0139 | -1.0 | 0.0254 | 0.1987 | 0.4875 | 0.4901 | 0.0122 | -1.0 | 0.3206 | 0.4875 | -1.0 | -1.0 |
| 0.8153 | 27.0 | 5643 | 0.8859 | 0.3207 | 0.7787 | 0.1897 | 0.3224 | 0.0139 | -1.0 | 0.0255 | 0.1991 | 0.4879 | 0.4905 | 0.0122 | -1.0 | 0.3207 | 0.4879 | -1.0 | -1.0 |
| 0.8153 | 28.0 | 5852 | 0.8862 | 0.3203 | 0.7785 | 0.1882 | 0.3222 | 0.0139 | -1.0 | 0.0255 | 0.1994 | 0.4867 | 0.4892 | 0.0122 | -1.0 | 0.3203 | 0.4867 | -1.0 | -1.0 |
| 0.8022 | 29.0 | 6061 | 0.8864 | 0.32 | 0.7776 | 0.1892 | 0.3219 | 0.0139 | -1.0 | 0.0253 | 0.1994 | 0.4871 | 0.4897 | 0.0122 | -1.0 | 0.32 | 0.4871 | -1.0 | -1.0 |
| 0.8022 | 30.0 | 6270 | 0.8865 | 0.32 | 0.778 | 0.1885 | 0.3219 | 0.0139 | -1.0 | 0.0252 | 0.1994 | 0.487 | 0.4896 | 0.0122 | -1.0 | 0.32 | 0.487 | -1.0 | -1.0 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|