End of training
Browse files- README.md +80 -0
- all_results.json +8 -0
- config.json +62 -0
- preprocessor_config.json +23 -0
- pytorch_model.bin +3 -0
- train_results.json +8 -0
- trainer_state.json +3682 -0
- training_args.bin +3 -0
README.md
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1 |
+
---
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+
license: apache-2.0
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+
base_model: microsoft/resnet-50
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tags:
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- generated_from_trainer
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datasets:
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- fair_face
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metrics:
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- accuracy
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model-index:
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- name: trained-age
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: fair_face
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type: fair_face
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config: '0.25'
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split: validation
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args: '0.25'
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.5164323534781815
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# trained-age
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the fair_face dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1340
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- Accuracy: 0.5164
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.3347 | 0.18 | 1000 | 1.3819 | 0.4296 |
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| 1.3071 | 0.37 | 2000 | 1.2799 | 0.4642 |
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| 1.297 | 0.55 | 3000 | 1.2503 | 0.4721 |
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| 1.3121 | 0.74 | 4000 | 1.1661 | 0.4995 |
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| 1.1806 | 0.92 | 5000 | 1.1137 | 0.5240 |
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| 1.0839 | 1.11 | 6000 | 1.1340 | 0.5164 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.14.0
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all_results.json
ADDED
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{
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2 |
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"epoch": 1.11,
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"total_flos": 2.0396723395200123e+18,
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4 |
+
"train_loss": 1.29178360859553,
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5 |
+
"train_runtime": 1561.0386,
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6 |
+
"train_samples_per_second": 222.273,
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+
"train_steps_per_second": 13.893
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}
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config.json
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{
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"_name_or_path": "microsoft/resnet-50",
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"architectures": [
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"ResNetForImageClassification"
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],
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"depths": [
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3,
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4,
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6,
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3
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],
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"downsample_in_first_stage": false,
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"embedding_size": 64,
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"hidden_act": "relu",
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"hidden_sizes": [
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256,
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512,
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1024,
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2048
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],
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"id2label": {
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"0": "0-2",
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"1": "3-9",
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"2": "10-19",
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"3": "20-29",
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"4": "30-39",
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"5": "40-49",
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"6": "50-59",
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"7": "60-69",
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"8": "more than 70"
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},
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"label2id": {
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"0-2": "0",
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"10-19": "2",
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"20-29": "3",
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"3-9": "1",
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"30-39": "4",
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"40-49": "5",
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"50-59": "6",
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"60-69": "7",
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"more than 70": "8"
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},
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"layer_type": "bottleneck",
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"model_type": "resnet",
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"num_channels": 3,
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"out_features": [
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"stage4"
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],
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"out_indices": [
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4
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],
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"problem_type": "single_label_classification",
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"stage_names": [
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"stem",
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"stage1",
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"stage2",
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"stage3",
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"stage4"
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],
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"torch_dtype": "float32",
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"transformers_version": "4.34.0"
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}
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preprocessor_config.json
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{
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"crop_pct": 0.875,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"feature_extractor_type": "ConvNextFeatureExtractor",
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_processor_type": "ConvNextFeatureExtractor",
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"shortest_edge": 224
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}
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}
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pytorch_model.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:12f330c4f743a48bb10df3a3c9ff27994e1c1dbbcb88450bb85e6104b181f7af
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size 94432333
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train_results.json
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{
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"epoch": 1.11,
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"total_flos": 2.0396723395200123e+18,
|
4 |
+
"train_loss": 1.29178360859553,
|
5 |
+
"train_runtime": 1561.0386,
|
6 |
+
"train_samples_per_second": 222.273,
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7 |
+
"train_steps_per_second": 13.893
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}
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trainer_state.json
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