End of training
Browse files- README.md +14 -6
- all_results.json +6 -6
- config.json +28 -28
- model.safetensors +1 -1
- train_results.json +6 -6
- trainer_state.json +2309 -32
- training_args.bin +1 -1
README.md
CHANGED
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@@ -22,7 +22,7 @@ model-index:
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metrics:
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- name: Accuracy
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type: accuracy
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-
value: 0.
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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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This model is a fine-tuned version of [microsoft/swin-large-patch4-window12-384-in22k](https://huggingface.co/microsoft/swin-large-patch4-window12-384-in22k) on the NIH-Xray dataset.
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It achieves the following results on the evaluation set:
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-
- Loss:
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-
- Accuracy: 0.
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## Model description
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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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- lr_scheduler_warmup_ratio: 0.1
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-
- num_epochs:
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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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-
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-
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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+
value: 0.49376114081996436
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| 26 |
---
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| 27 |
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| 28 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [microsoft/swin-large-patch4-window12-384-in22k](https://huggingface.co/microsoft/swin-large-patch4-window12-384-in22k) on the NIH-Xray dataset.
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| 34 |
It achieves the following results on the evaluation set:
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| 35 |
+
- Loss: 3.7711
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| 36 |
+
- Accuracy: 0.4938
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| 37 |
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| 38 |
## Model description
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| 39 |
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| 61 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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+
- num_epochs: 10
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### Training results
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| 67 |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| 69 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
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| 70 |
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| 1.8318 | 0.9984 | 315 | 1.7651 | 0.5437 |
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| 71 |
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| 1.6067 | 2.0 | 631 | 1.6393 | 0.5455 |
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| 1.406 | 2.9984 | 946 | 1.6472 | 0.5490 |
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| 1.3983 | 4.0 | 1262 | 1.7344 | 0.5455 |
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| 0.7272 | 4.9984 | 1577 | 2.1283 | 0.5258 |
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| 0.3975 | 6.0 | 1893 | 2.5229 | 0.5134 |
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| 0.2648 | 6.9984 | 2208 | 3.0333 | 0.5080 |
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| 0.1232 | 8.0 | 2524 | 3.4626 | 0.5241 |
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| 0.0873 | 8.9984 | 2839 | 3.6219 | 0.5027 |
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| 0.0554 | 9.9842 | 3150 | 3.7711 | 0.4938 |
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### Framework versions
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all_results.json
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{
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"epoch":
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"total_flos":
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"train_loss":
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second": 0.
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}
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{
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"epoch": 9.984152139461173,
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"total_flos": 2.6101205954547646e+19,
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"train_loss": 0.7937991834822156,
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+
"train_runtime": 16586.4479,
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"train_samples_per_second": 3.042,
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"train_steps_per_second": 0.19
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}
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config.json
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"hidden_dropout_prob": 0.0,
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"hidden_size": 1536,
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"id2label": {
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-
"0": "
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"1": "
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"2": "
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"3": "No Finding",
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"4": "
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"5": "
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"6": "
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"12": "
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"13": "
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"14": "
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},
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"image_size": 384,
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"initializer_range": 0.02,
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"label2id": {
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"Atelectasis":
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"Cardiomegaly":
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"Consolidation":
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"Edema":
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"Effusion":
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"Emphysema":
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"Fibrosis":
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"Hernia":
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"Infiltration":
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"Mass":
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"No Finding": 3,
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"Nodule":
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"Pleural_Thickening":
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"Pneumonia":
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"Pneumothorax":
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},
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"layer_norm_eps": 1e-05,
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"mlp_ratio": 4.0,
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"hidden_dropout_prob": 0.0,
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"hidden_size": 1536,
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"id2label": {
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"0": "Pleural_Thickening",
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"1": "Pneumothorax",
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"2": "Effusion",
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"3": "No Finding",
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"4": "Infiltration",
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"5": "Mass",
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"6": "Nodule",
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"7": "Emphysema",
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"8": "Edema",
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"9": "Fibrosis",
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"10": "Cardiomegaly",
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"11": "Atelectasis",
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"12": "Pneumonia",
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"13": "Hernia",
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"14": "Consolidation"
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},
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"image_size": 384,
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"initializer_range": 0.02,
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"label2id": {
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"Atelectasis": 11,
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"Cardiomegaly": 10,
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"Consolidation": 14,
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"Edema": 8,
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"Effusion": 2,
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"Emphysema": 7,
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"Fibrosis": 9,
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"Hernia": 13,
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"Infiltration": 4,
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"Mass": 5,
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"No Finding": 3,
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"Nodule": 6,
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"Pleural_Thickening": 0,
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"Pneumonia": 12,
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"Pneumothorax": 1
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},
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"layer_norm_eps": 1e-05,
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"mlp_ratio": 4.0,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 784924668
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:1daf5f592fb81d4eaa196e6f9effdf921903e8b0e265602e423583bae3acb1b4
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size 784924668
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train_results.json
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{
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-
"epoch":
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"total_flos":
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"train_loss":
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"train_runtime":
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"train_samples_per_second":
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"train_steps_per_second": 0.
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}
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{
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"epoch": 9.984152139461173,
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"total_flos": 2.6101205954547646e+19,
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"train_loss": 0.7937991834822156,
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"train_runtime": 16586.4479,
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"train_samples_per_second": 3.042,
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"train_steps_per_second": 0.19
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}
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trainer_state.json
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{
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"best_metric": 0.
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"best_model_checkpoint": "SwinLarge/checkpoint-
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"epoch":
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"eval_steps": 500,
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"global_step":
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"log_history": [
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{
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