Instructions to use skumar1998/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skumar1998/result with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("skumar1998/result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Training in progress, step 6
Browse files- README.md +1 -1
- adapter_config.json +2 -2
- adapter_model.safetensors +2 -2
- distribution.json +1 -1
- doctype_entity_distribution.json +24 -23
- entity_distribution.json +24 -23
- file.log +42 -43
- ground_truth_data.json +0 -0
- gt_json.json +117 -145
- runs/Jul24_09-37-50_0338beef2735/events.out.tfevents.1784885870.0338beef2735.7321.0 +3 -0
- sorted_distribution.json +1 -1
- split_statistics.json +1 -1
- training_args.bin +1 -1
README.md
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model_name: result
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tags:
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- generated_from_trainer
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- sft
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- unsloth
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licence: license
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---
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model_name: result
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tags:
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- generated_from_trainer
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- trl
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- sft
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- unsloth
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licence: license
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---
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adapter_config.json
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"peft_type": "LORA",
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"peft_version": "0.19.1",
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"qalora_group_size": 16,
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"r":
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"rank_pattern": {},
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"revision": null,
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"target_modules": "(?:.*?(?:vision|image|visual|patch|language|text).*?(?:self_attn|attention|attn|mixer|mlp|feed_forward|ffn|dense|mixer).*?(?:qkv|proj|linear_fc1|linear_fc2|out_proj|in_proj_qkv|in_proj_z|in_proj_b|in_proj_a|gate_proj|up_proj|down_proj|q_proj|k_proj|v_proj|o_proj))|(?:\\bmodel\\.layers\\.[\\d]{1,}\\.(?:self_attn|attention|attn|mixer|mlp|feed_forward|ffn|dense|mixer)\\.(?:(?:qkv|proj|linear_fc1|linear_fc2|out_proj|in_proj_qkv|in_proj_z|in_proj_b|in_proj_a|gate_proj|up_proj|down_proj|q_proj|k_proj|v_proj|o_proj)))",
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"layers_pattern": null,
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"loftq_config": {},
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"lora_alpha": 128,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"lora_ga_config": null,
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"peft_type": "LORA",
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"peft_version": "0.19.1",
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"qalora_group_size": 16,
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"r": 64,
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"rank_pattern": {},
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"revision": null,
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"target_modules": "(?:.*?(?:vision|image|visual|patch|language|text).*?(?:self_attn|attention|attn|mixer|mlp|feed_forward|ffn|dense|mixer).*?(?:qkv|proj|linear_fc1|linear_fc2|out_proj|in_proj_qkv|in_proj_z|in_proj_b|in_proj_a|gate_proj|up_proj|down_proj|q_proj|k_proj|v_proj|o_proj))|(?:\\bmodel\\.layers\\.[\\d]{1,}\\.(?:self_attn|attention|attn|mixer|mlp|feed_forward|ffn|dense|mixer)\\.(?:(?:qkv|proj|linear_fc1|linear_fc2|out_proj|in_proj_qkv|in_proj_z|in_proj_b|in_proj_a|gate_proj|up_proj|down_proj|q_proj|k_proj|v_proj|o_proj)))",
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distribution.json
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"other_insurance_name_1": 16,
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"patient.city": 29,
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"patient.middle_name": 18,
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"patient.state": 29,
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"patient.zip": 41,
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"facility.address": 53,
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"other_insurance_name_1": 16,
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"patient.middle_name": 18,
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"accession_number": 11,
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"collection_date": 28,
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"provider_npi": 36,
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2026-07-24 09:04:27.854 | INFO | app.tasks.entity.vlm.model:train_model:527 - training complete: TrainOutput(global_step=130, training_loss=0.07528288119400924, metrics={'train_runtime': 3399.9478, 'train_samples_per_second': 0.306, 'train_steps_per_second': 0.038, 'total_flos': 3.1486185084423456e+17, 'train_loss': 0.07528288119400924, 'epoch': 9.290909090909091})
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2026-07-24 09:34:49.040 | INFO | app.tasks.entity.vlm.dataset:create:650 - Using pre-split dataset mode
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2026-07-24 09:34:49.057 | INFO | app.tasks.entity.vlm.dataset:_download_current_splits:1565 - Downloading train dataset from s3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a632d4-6217-73a7-8000-371ca6dde2d0/train.json
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2026-07-24 09:34:49.390 | INFO | app.tasks.entity.vlm.dataset:_download_split_documents:1422 - Processing %s %s/%s with %d documents
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2026-07-24 09:34:50.413 | INFO | app.tasks.entity.vlm.dataset:_download_current_splits:1565 - Downloading val dataset from s3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a632d4-6217-73a7-8000-371ca6dde2d0/eval.json
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2026-07-24 09:34:50.647 | INFO | app.tasks.entity.vlm.dataset:_download_split_documents:1422 - Processing %s %s/%s with %d documents
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2026-07-24 09:34:51.242 | INFO | app.tasks.entity.vlm.dataset:_download_current_splits:1565 - Downloading test dataset from s3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a632d4-6217-73a7-8000-371ca6dde2d0/test.json
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2026-07-24 09:34:51.520 | INFO | app.tasks.entity.vlm.dataset:_download_split_documents:1422 - Processing %s %s/%s with %d documents
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2026-07-24 09:34:52.207 | INFO | app.tasks.entity.vlm.dataset:_download_miscellaneous:1612 - Downloading miscellaneous data from s3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a632d4-6217-73a7-8000-371ca6dde2d0/miscellaneous.json
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2026-07-24 09:34:52.465 | INFO | app.tasks.entity.vlm.dataset:_download_previous_datasets:1521 - Found 0 previous dataset(s) to consolidate
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2026-07-24 09:34:52.466 | INFO | app.tasks.entity.vlm.dataset:download_presplit_datasets:1663 - Successfully downloaded all datasets to /home/ubuntu/dataset
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2026-07-24 09:34:53.185 | INFO | app.tasks.entity.vlm.dataset:remove_null_files:574 - Removed 0 files with null values
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2026-07-24 09:34:53.261 | INFO | app.tasks.entity.vlm.reports:get_distribution:1513 - Original number of ground truth files 120
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2026-07-24 09:34:53.480 | INFO | app.tasks.entity.vlm.reports:get_distribution:1528 - After removing empty files 120
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2026-07-24 09:34:53.499 | INFO | app.tasks.entity.vlm.reports:get_entity_distribution:1628 - Creating entity distribution for 120 files
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2026-07-24 09:34:53.820 | DEBUG | app.commonmlops:get_oauth_token:834 - OAuth token request status: 200
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2026-07-24 09:34:54.098 | DEBUG | app.commonmlops:get_training_job_queue:891 - Get training job queue status code: 200, api_url: https://aitest.api.dexit.tech/api/v1/mlops/trainingjobqueue/06a632d8-22dc-7d70-8000-ad2feb7176cf
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2026-07-24 09:34:54.257 | DEBUG | app.commonmlops:get_oauth_token:834 - OAuth token request status: 200
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2026-07-24 09:34:54.258 | DEBUG | app.commonmlops:update_training_job_queue:937 - Updating training job queue with merged payload: {'id': '06a632d8-22dc-7d70-8000-ad2feb7176cf', 'modeltype': 'entity', 'modelname': 'vlm_qwen3_5', 'jobtype': 'feedback', 'basemodelversionid': '019f0d56-3844-7c0a-8fab-4aa6a6d1f12e', 'datasetid': '06a632d4-6217-73a7-8000-371ca6dde2d0', 'status': 'triggered', 'createddate': '2026-07-24T09:16:50.178958Z', 'createdby': '00000000-0000-0000-0000-000000000000', 'startdate': '2026-07-24T09:34:14.848339Z', 'enddate': None, 'accuracyreport': None, 'metadata': {'clearml_details': {'hf_model_id': '314e/dexit-aitest-vlm_qwen3_6-entity-integration', 'clearml_task_id': 'b20dd082c6a14594a8147f2971d40e0b', 'new_modelversion_tag': 'v0.0.0', 'base_modelversion_tag': 'v0.0.0', 'trained_entities': ['accession_number', 'collection_date', 'facility.address', 'facility.city', 'facility.name', 'facility.state', 'facility.zip', 'medicaid_insurance_number', 'medicare_insurance_number', 'other_insurance_name_1', 'other_insurance_name_2', 'other_insurance_number_1', 'other_insurance_number_2', 'patient.address', 'patient.city', 'patient.dob', 'patient.first_name', 'patient.last_name', 'patient.middle_name', 'patient.sex', 'patient.state', 'patient.zip', 'phone_number', 'provider_npi', 'sample_code', 'social_security_number']}, 'hyperparameters': {'DATASET_PARAMS': {'DATASET__EVAL_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a632d4-6217-73a7-8000-371ca6dde2d0/eval.json', 'DATASET__TEST_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a632d4-6217-73a7-8000-371ca6dde2d0/test.json', 'DATASET__TRAIN_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a632d4-6217-73a7-8000-371ca6dde2d0/train.json', 'DATASET__MISCELLANEOUS_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a632d4-6217-73a7-8000-371ca6dde2d0/miscellaneous.json'}, 'MODEL_CONFIGURATION': {'SEED': 42, 'MODELNAME': 'vlm_qwen3_6', 'MODELTYPE': 'entity', 'ENVIRONMENT': 'integration', 'HF_MODEL_ID': '314e/dexit-aitest-vlm_qwen3_6-entity-integration', 'MODEL_FAMILY': 'qwen', 'ARTIFACTS_DIR': '/home/ubuntu/result', 'MODELVERSIONTAG': 'v0.0.0', 'HF_BASE_MODEL_ID': 'Qwen/Qwen3.6-27B', 'IMAGE_PATCH_SIZE': 16, 'THRESHOLD_OFFSET': 0.05, 'TRAIN_OOTB_MODEL': True, 'NEW_MODELVERSIONTAG': 'v0.0.0'}, 'MODEL_HYPERPARAMETERS': {'RANK': 64, 'ALPHA': 128, 'TRAIN_EPOCHS': 2, 'EVAL_BATCH_SIZE': 1, 'GRAD_ACCUM_STEPS': 4, 'TRAIN_BATCH_SIZE': 2, 'INFERENCE_BATCH_SIZE': 1}}, 'workflow_details': {'temporal_workflow_id': 'local-model-retraining-entity-f05c9f4e', 'skypilot_cluster_name': 'dexit-aitest-skypilot-entity-1784884909-826023', 'temporal_workflow_run_id': '019f936e-27c5-7dc7-a6ea-f588f75914eb'}, 'modelconfig_snapshot': {'modelname': 'vlm_qwen3_6', 'modeltype': 'entity', 'deployment': {'auto_model_deployment_manual': False, 'auto_model_deployment_feedback': False}, 'feedback_config': {'bucket_low': 0.5, 'bucket_high': 0.7, 'auto_trigger_retraining': True, 'non_corrected_sample_ratio': 0.5, 'min_feedback_count_for_retraining': 1500, 'low_bucket_threshold_offset_multiplier': 0.5, 'auto_trigger_retraining_on_new_entities': False, 'high_bucket_threshold_offset_multiplier': 1.5, 'low_precision_bucket_corrected_sample_rate': 0.8, 'mid_precision_bucket_corrected_sample_rate': 0.5, 'high_precision_bucket_corrected_sample_rate': 0.2, 'low_precision_bucket_threshold_sample_count': 100}, 'training_config': {'seed': 42, 'dataset': {'eval_size': 0.1, 'test_size': 0.2, 'train_size': 0.7}, 'cloud_providers': [{'accelerators': ['A100-80GB:1', 'H100:1'], 'provider_name': 'runpod'}], 'hyperparameters': {'rank': 64, 'alpha': 128, 'train_epochs': 2, 'grad_accum_steps': 4, 'train_batch_size': 2}, 'hf_base_model_id': 'Qwen/Qwen3.6-27B', 'train_ootb_model': True, 'previous_datasets': {'eval': {'enabled': True, 'distribution': {'weights': {'n-1': 1.0}, 'strategy': 'equal', 'decay_factor': 0.8}, 'max_versions_to_include': 'all'}, 'test': {'enabled': True, 'distribution': {'weights': {'n-1': 1.0}, 'strategy': 'equal', 'decay_factor': 0.8}, 'max_versions_to_include': 'all'}, 'train': {'enabled': True, 'distribution': {'weights': {'n-1': 1.0}, 'strategy': 'equal', 'decay_factor': 0.8}, 'max_versions_to_include': 'all'}}}, 'threshold_offset': 0.05}}, 'deploymentstatus': None, 'deployeddate': None}
|
| 19 |
+
2026-07-24 09:34:54.427 | DEBUG | app.commonmlops:update_training_job_queue:940 - Update training job queue status code: 200, api_url: https://aitest.api.dexit.tech/api/v1/mlops/trainingjobqueue/06a632d8-22dc-7d70-8000-ad2feb7176cf
|
| 20 |
+
2026-07-24 09:34:54.429 | SUCCESS | app.commonmlops:update_trained_entities:979 - Updated trained_entities on training job queue
|
| 21 |
+
2026-07-24 09:34:55.122 | INFO | app.tasks.entity.vlm.reports:upload_initial_artifacts:1696 - Uploaded intial artifacts to ClearML
|
| 22 |
+
2026-07-24 09:34:55.123 | INFO | __main__:_run_training_phase:657 - Moving into standard training loop
|
| 23 |
+
2026-07-24 09:34:55.124 | INFO | __main__:setup_directories:211 - Loading pre-split dataset statistics
|
| 24 |
+
2026-07-24 09:34:55.229 | INFO | __main__:load_presplit_statistics:188 - Found 83 training samples
|
| 25 |
+
2026-07-24 09:34:55.279 | INFO | __main__:load_presplit_statistics:190 - Found 24 test samples
|
| 26 |
+
2026-07-24 09:34:55.317 | INFO | __main__:load_presplit_statistics:192 - Found 13 validation samples
|
| 27 |
+
2026-07-24 09:34:55.317 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:986 -
|
| 28 |
Dataset Split Statistics:
|
| 29 |
+
2026-07-24 09:34:55.318 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:987 - Total samples: 120
|
| 30 |
+
2026-07-24 09:34:55.318 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:989 - Train set: 83 (69.2%)
|
| 31 |
+
2026-07-24 09:34:55.318 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:990 - Test set: 24 (20.0%)
|
| 32 |
+
2026-07-24 09:34:55.319 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:991 - Validation set: 13 (10.8%)
|
| 33 |
+
2026-07-24 09:34:55.320 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:1000 - Split statistics saved to /home/ubuntu/result/split_statistics.json
|
| 34 |
+
2026-07-24 09:34:55.323 | INFO | __main__:standard_training_loop:354 - Initializing model
|
| 35 |
+
2026-07-24 09:34:55.324 | INFO | __main__:initialize_model:243 - Setting up model for retraining
|
| 36 |
+
2026-07-24 09:34:55.324 | INFO | __main__:initialize_model:246 - Training from base model: Qwen/Qwen3.6-27B
|
| 37 |
+
2026-07-24 09:34:55.324 | INFO | app.tasks.entity.vlm.model:__post_init__:227 - loading model Qwen/Qwen3.6-27B for training with unsloth
|
| 38 |
+
2026-07-24 09:37:38.205 | INFO | app.tasks.entity.vlm.model:calculate_max_steps:323 - num_samples: 83, batch_size: 2, gradient_accumulation_steps: 4, epochs: 2
|
| 39 |
+
2026-07-24 09:37:38.206 | INFO | app.tasks.entity.vlm.model:calculate_max_steps:327 - calculating max steps
|
| 40 |
+
2026-07-24 09:37:38.255 | INFO | __main__:standard_training_loop:357 - Setting up trainer
|
| 41 |
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2026-07-24 09:37:47.271 | INFO | __main__:create_trainer:306 - Materialized datasets: 83 train, 13 eval samples
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| 42 |
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2026-07-24 09:37:47.930 | INFO | __main__:standard_training_loop:360 - Starting training
|
| 43 |
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2026-07-24 09:37:48.282 | INFO | app.tasks.entity.vlm.model:train_model:528 - everything is set up, launching training
|
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{
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"gt_jsons": [
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"/home/ubuntu/dataset/train/facesheet/
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"/home/ubuntu/dataset/train/facesheet/0696090f-d74e-7578-8000-f420429cf9a5.json",
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"/home/ubuntu/dataset/train/facesheet/0696090f-
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}
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|
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|
| 119 |
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|
| 120 |
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|
| 121 |
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|
| 122 |
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| 123 |
]
|
| 124 |
}
|
runs/Jul24_09-37-50_0338beef2735/events.out.tfevents.1784885870.0338beef2735.7321.0
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 9179
|
sorted_distribution.json
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
{
|
| 2 |
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"facesheet":
|
| 3 |
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|
|
|
|
| 1 |
{
|
| 2 |
+
"facesheet": 120
|
| 3 |
}
|
split_statistics.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
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{"total":
|
|
|
|
| 1 |
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{"total": 120, "train": 83, "test": 24, "val": 13}
|
training_args.bin
CHANGED
|
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|
| 1 |
version https://git-lfs.github.com/spec/v1
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| 2 |
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| 3 |
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|
| 1 |
version https://git-lfs.github.com/spec/v1
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| 3 |
size 5905
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