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 79
Browse files- README.md +3 -3
- adapter_config.json +2 -1
- adapter_model.safetensors +1 -1
- doctype_entity_distribution.json +10 -10
- entity_distribution.json +10 -10
- file.log +42 -43
- ground_truth_data.json +0 -0
- gt_json.json +0 -0
- runs/Sep28_11-24-35_191e889c7694/events.out.tfevents.1790594675.191e889c7694.10027.0 +3 -0
- training_args.bin +1 -1
README.md
CHANGED
|
@@ -4,8 +4,8 @@ library_name: transformers
|
|
| 4 |
model_name: result
|
| 5 |
tags:
|
| 6 |
- generated_from_trainer
|
| 7 |
-
- sft
|
| 8 |
- unsloth
|
|
|
|
| 9 |
- trl
|
| 10 |
licence: license
|
| 11 |
---
|
|
@@ -21,7 +21,7 @@ It has been trained using [TRL](https://github.com/huggingface/trl).
|
|
| 21 |
from transformers import pipeline
|
| 22 |
|
| 23 |
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
|
| 24 |
-
generator = pipeline("text-generation", model="skumar1998/result",
|
| 25 |
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
|
| 26 |
print(output["generated_text"])
|
| 27 |
```
|
|
@@ -36,7 +36,7 @@ This model was trained with SFT.
|
|
| 36 |
|
| 37 |
### Framework versions
|
| 38 |
|
| 39 |
-
- TRL: 1.
|
| 40 |
- Transformers: 5.14.1
|
| 41 |
- Pytorch: 2.7.1
|
| 42 |
- Datasets: 4.3.0
|
|
|
|
| 4 |
model_name: result
|
| 5 |
tags:
|
| 6 |
- generated_from_trainer
|
|
|
|
| 7 |
- unsloth
|
| 8 |
+
- sft
|
| 9 |
- trl
|
| 10 |
licence: license
|
| 11 |
---
|
|
|
|
| 21 |
from transformers import pipeline
|
| 22 |
|
| 23 |
question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
|
| 24 |
+
generator = pipeline("text-generation", model="skumar1998/result", device_map="auto")
|
| 25 |
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
|
| 26 |
print(output["generated_text"])
|
| 27 |
```
|
|
|
|
| 36 |
|
| 37 |
### Framework versions
|
| 38 |
|
| 39 |
+
- TRL: 1.14.0
|
| 40 |
- Transformers: 5.14.1
|
| 41 |
- Pytorch: 2.7.1
|
| 42 |
- Datasets: 4.3.0
|
adapter_config.json
CHANGED
|
@@ -16,6 +16,7 @@
|
|
| 16 |
"fan_in_fan_out": false,
|
| 17 |
"inference_mode": true,
|
| 18 |
"init_lora_weights": true,
|
|
|
|
| 19 |
"layer_replication": null,
|
| 20 |
"layers_pattern": null,
|
| 21 |
"layers_to_transform": null,
|
|
@@ -29,7 +30,7 @@
|
|
| 29 |
"modules_to_save": null,
|
| 30 |
"monteclora_config": null,
|
| 31 |
"peft_type": "LORA",
|
| 32 |
-
"peft_version": "0.
|
| 33 |
"qalora_group_size": 16,
|
| 34 |
"r": 256,
|
| 35 |
"rank_pattern": {},
|
|
|
|
| 16 |
"fan_in_fan_out": false,
|
| 17 |
"inference_mode": true,
|
| 18 |
"init_lora_weights": true,
|
| 19 |
+
"kasa_config": null,
|
| 20 |
"layer_replication": null,
|
| 21 |
"layers_pattern": null,
|
| 22 |
"layers_to_transform": null,
|
|
|
|
| 30 |
"modules_to_save": null,
|
| 31 |
"monteclora_config": null,
|
| 32 |
"peft_type": "LORA",
|
| 33 |
+
"peft_version": "0.21.0",
|
| 34 |
"qalora_group_size": 16,
|
| 35 |
"r": 256,
|
| 36 |
"rank_pattern": {},
|
adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 7470734200
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7a6f87bb4f9c50489b4e58ba8cf111289298524d2495a9059698e6ea67142903
|
| 3 |
size 7470734200
|
doctype_entity_distribution.json
CHANGED
|
@@ -1,29 +1,29 @@
|
|
| 1 |
{
|
| 2 |
"facesheet": {
|
| 3 |
-
"accession_number": 1513,
|
| 4 |
-
"collection_date": 2801,
|
| 5 |
"facility_address": 5652,
|
| 6 |
"facility_city": 5678,
|
| 7 |
"facility_name": 5647,
|
| 8 |
"facility_state": 5694,
|
| 9 |
"facility_zip": 5721,
|
| 10 |
-
"
|
| 11 |
"other_insurance_number_1": 1967,
|
|
|
|
|
|
|
| 12 |
"patient_dob": 5673,
|
| 13 |
"patient_first_name": 6051,
|
| 14 |
"patient_last_name": 6056,
|
| 15 |
"patient_sex": 5636,
|
| 16 |
-
"provider_npi": 5017,
|
| 17 |
-
"sample_code": 5012,
|
| 18 |
-
"medicaid_insurance_number": 2052,
|
| 19 |
-
"medicare_insurance_number": 1597,
|
| 20 |
-
"patient_address": 2303,
|
| 21 |
-
"patient_city": 2321,
|
| 22 |
-
"patient_middle_name": 974,
|
| 23 |
"patient_state": 2429,
|
| 24 |
"patient_zip": 2363,
|
| 25 |
"phone_number": 1269,
|
|
|
|
|
|
|
|
|
|
| 26 |
"social_security_number": 180,
|
|
|
|
|
|
|
|
|
|
|
|
|
| 27 |
"other_insurance_name_2": 17,
|
| 28 |
"other_insurance_number_2": 18
|
| 29 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"facesheet": {
|
|
|
|
|
|
|
| 3 |
"facility_address": 5652,
|
| 4 |
"facility_city": 5678,
|
| 5 |
"facility_name": 5647,
|
| 6 |
"facility_state": 5694,
|
| 7 |
"facility_zip": 5721,
|
| 8 |
+
"medicaid_insurance_number": 2052,
|
| 9 |
"other_insurance_number_1": 1967,
|
| 10 |
+
"patient_address": 2303,
|
| 11 |
+
"patient_city": 2321,
|
| 12 |
"patient_dob": 5673,
|
| 13 |
"patient_first_name": 6051,
|
| 14 |
"patient_last_name": 6056,
|
| 15 |
"patient_sex": 5636,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
"patient_state": 2429,
|
| 17 |
"patient_zip": 2363,
|
| 18 |
"phone_number": 1269,
|
| 19 |
+
"medicare_insurance_number": 1597,
|
| 20 |
+
"other_insurance_name_1": 1962,
|
| 21 |
+
"patient_middle_name": 974,
|
| 22 |
"social_security_number": 180,
|
| 23 |
+
"accession_number": 1513,
|
| 24 |
+
"collection_date": 2801,
|
| 25 |
+
"provider_npi": 5017,
|
| 26 |
+
"sample_code": 5012,
|
| 27 |
"other_insurance_name_2": 17,
|
| 28 |
"other_insurance_number_2": 18
|
| 29 |
}
|
entity_distribution.json
CHANGED
|
@@ -1,28 +1,28 @@
|
|
| 1 |
{
|
| 2 |
-
"accession_number": 1513,
|
| 3 |
-
"collection_date": 2801,
|
| 4 |
"facility_address": 5652,
|
| 5 |
"facility_city": 5678,
|
| 6 |
"facility_name": 5647,
|
| 7 |
"facility_state": 5694,
|
| 8 |
"facility_zip": 5721,
|
| 9 |
-
"
|
| 10 |
"other_insurance_number_1": 1967,
|
|
|
|
|
|
|
| 11 |
"patient_dob": 5673,
|
| 12 |
"patient_first_name": 6051,
|
| 13 |
"patient_last_name": 6056,
|
| 14 |
"patient_sex": 5636,
|
| 15 |
-
"provider_npi": 5017,
|
| 16 |
-
"sample_code": 5012,
|
| 17 |
-
"medicaid_insurance_number": 2052,
|
| 18 |
-
"medicare_insurance_number": 1597,
|
| 19 |
-
"patient_address": 2303,
|
| 20 |
-
"patient_city": 2321,
|
| 21 |
-
"patient_middle_name": 974,
|
| 22 |
"patient_state": 2429,
|
| 23 |
"patient_zip": 2363,
|
| 24 |
"phone_number": 1269,
|
|
|
|
|
|
|
|
|
|
| 25 |
"social_security_number": 180,
|
|
|
|
|
|
|
|
|
|
|
|
|
| 26 |
"other_insurance_name_2": 17,
|
| 27 |
"other_insurance_number_2": 18
|
| 28 |
}
|
|
|
|
| 1 |
{
|
|
|
|
|
|
|
| 2 |
"facility_address": 5652,
|
| 3 |
"facility_city": 5678,
|
| 4 |
"facility_name": 5647,
|
| 5 |
"facility_state": 5694,
|
| 6 |
"facility_zip": 5721,
|
| 7 |
+
"medicaid_insurance_number": 2052,
|
| 8 |
"other_insurance_number_1": 1967,
|
| 9 |
+
"patient_address": 2303,
|
| 10 |
+
"patient_city": 2321,
|
| 11 |
"patient_dob": 5673,
|
| 12 |
"patient_first_name": 6051,
|
| 13 |
"patient_last_name": 6056,
|
| 14 |
"patient_sex": 5636,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 15 |
"patient_state": 2429,
|
| 16 |
"patient_zip": 2363,
|
| 17 |
"phone_number": 1269,
|
| 18 |
+
"medicare_insurance_number": 1597,
|
| 19 |
+
"other_insurance_name_1": 1962,
|
| 20 |
+
"patient_middle_name": 974,
|
| 21 |
"social_security_number": 180,
|
| 22 |
+
"accession_number": 1513,
|
| 23 |
+
"collection_date": 2801,
|
| 24 |
+
"provider_npi": 5017,
|
| 25 |
+
"sample_code": 5012,
|
| 26 |
"other_insurance_name_2": 17,
|
| 27 |
"other_insurance_number_2": 18
|
| 28 |
}
|
file.log
CHANGED
|
@@ -1,44 +1,43 @@
|
|
| 1 |
-
2026-
|
| 2 |
-
2026-
|
| 3 |
-
2026-
|
| 4 |
-
2026-
|
| 5 |
-
2026-
|
| 6 |
-
2026-
|
| 7 |
-
2026-
|
| 8 |
-
2026-
|
| 9 |
-
2026-
|
| 10 |
-
2026-
|
| 11 |
-
2026-
|
| 12 |
-
2026-
|
| 13 |
-
2026-
|
| 14 |
-
2026-
|
| 15 |
-
2026-
|
| 16 |
-
2026-
|
| 17 |
-
2026-
|
| 18 |
-
2026-08-23 12:33:27.035 | DEBUG | app.commonmlops:update_training_job_queue:937 - Updating training job queue with merged payload: {'id': '06a665f8-ebd0-7481-8000-83304d751ace', 'modeltype': 'entity', 'modelname': 'vlm_qwen3_6', 'jobtype': 'feedback', 'basemodelversionid': '019f0d56-3844-7c0a-8fab-4aa6a6d1f12e', 'datasetid': '06a665f5-06bf-7f15-8000-acbbe709e051', 'status': 'triggered', 'createddate': '2026-07-26T19:27:10.738422Z', 'createdby': '00000000-0000-0000-0000-000000000000', 'startdate': '2026-08-23T12:31:23.779701Z', 'enddate': None, 'accuracyreport': {'overall': {'recall': 0.9489486112672889, 'f1_score': 0.9511143670226255, 'precision': 0.953290031064671}, 'patient': {'recall': 0.9570468593654881, 'accuracy': 0.965850180851059, 'f1_score': 0.9578867442511313, 'precision': 0.9588553005522813}, 'facility': {'recall': 0.9681215596546779, 'accuracy': 0.9468811825459762, 'f1_score': 0.9706030656585861, 'precision': 0.9731011770220469}, 'patient-dob': {'recall': 0.9812606473594548, 'accuracy': 0.9683042789223455, 'f1_score': 0.9829351535836178, 'precision': 0.9846153846153847}, 'patient-sex': {'recall': 0.9982847341337907, 'accuracy': 0.9967871485943776, 'f1_score': 0.9982847341337907, 'precision': 0.9982847341337907}, 'patient-zip': {'recall': 0.9623762376237623, 'accuracy': 0.9839486356340289, 'f1_score': 0.9798387096774194, 'precision': 0.997946611909651}, 'patient.dob': {'recall': 0.9821124361158433, 'accuracy': 0.9706582077716098, 'f1_score': 0.9842082799829279, 'precision': 0.9863130881094953}, 'patient.sex': {'recall': 0.9991423670668954, 'accuracy': 0.9983935742971888, 'f1_score': 0.9991423670668954, 'precision': 0.9991423670668954}, 'patient.zip': {'recall': 0.9663366336633663, 'accuracy': 0.9847512038523274, 'f1_score': 0.9809045226130653, 'precision': 0.9959183673469387}, 'sample-code': {'recall': 0.9737609329446064, 'accuracy': 0.9545454545454546, 'f1_score': 0.9732880038853812, 'precision': 0.9728155339805825}, 'facility-zip': {'recall': 0.9796782387806944, 'accuracy': 0.9728434504792333, 'f1_score': 0.985519591141397, 'precision': 0.9914310197086547}, 'facility.zip': {'recall': 0.9847586790855207, 'accuracy': 0.9808, 'f1_score': 0.9897872340425531, 'precision': 0.9948674080410608}, 'patient-city': {'recall': 0.9756592292089249, 'accuracy': 0.9864, 'f1_score': 0.982635342185904, 'precision': 0.9897119341563786}, 'patient.city': {'recall': 0.9817444219066938, 'accuracy': 0.988, 'f1_score': 0.9847405900305187, 'precision': 0.9877551020408163}, 'phone-number': {'recall': 0.9784172661870504, 'accuracy': 0.9847756410256411, 'f1_score': 0.9662522202486679, 'precision': 0.9543859649122807}, 'provider-npi': {'recall': 1.0, 'accuracy': 0.9991546914623838, 'f1_score': 0.9995147986414362, 'precision': 0.9990300678952473}, 'facility-city': {'recall': 0.9931682322801024, 'accuracy': 0.9903691813804173, 'f1_score': 0.9948674080410608, 'precision': 0.9965724078834619}, 'facility-name': {'recall': 0.9692570452604612, 'accuracy': 0.9460093896713615, 'f1_score': 0.9705002137665669, 'precision': 0.9717465753424658}, 'facility.city': {'recall': 0.9965841161400513, 'accuracy': 0.9967871485943776, 'f1_score': 0.998289136013687, 'precision': 1.0}, 'facility.name': {'recall': 0.9624252775405636, 'accuracy': 0.9339035769828927, 'f1_score': 0.9636596836254809, 'precision': 0.9648972602739726}, 'patient-state': {'recall': 0.7729007633587787, 'accuracy': 0.8273062730627306, 'f1_score': 0.7758620689655172, 'precision': 0.7788461538461539}, 'patient.state': {'recall': 0.8530534351145038, 'accuracy': 0.8843226788432268, 'f1_score': 0.8546845124282982, 'precision': 0.8563218390804598}, 'facility-state': {'recall': 0.8662691652470187, 'accuracy': 0.7794540229885057, 'f1_score': 0.8688594617684751, 'precision': 0.87146529562982}, 'facility.state': {'recall': 0.9335604770017035, 'accuracy': 0.8867781155015197, 'f1_score': 0.936351986330628, 'precision': 0.9391602399314481}, 'collection-date': {'recall': 0.8938053097345132, 'accuracy': 0.9175597691673537, 'f1_score': 0.9099099099099099, 'precision': 0.926605504587156}, 'patient-address': {'recall': 0.8693877551020408, 'accuracy': 0.9042145593869731, 'f1_score': 0.872057318321392, 'precision': 0.8747433264887063}, 'patient.address': {'recall': 0.9, 'accuracy': 0.9255813953488372, 'f1_score': 0.901840490797546, 'precision': 0.9036885245901639}, 'accession-number': {'recall': 0.9967948717948718, 'accuracy': 0.9991546914623838, 'f1_score': 0.9983948635634029, 'precision': 1.0}, 'facility-address': {'recall': 0.9513236549957301, 'accuracy': 0.9173106646058733, 'f1_score': 0.9541755888650965, 'precision': 0.9570446735395189}, 'facility.address': {'recall': 0.9632792485055508, 'accuracy': 0.9361370716510904, 'f1_score': 0.9649272882805817, 'precision': 0.9665809768637532}, 'patient-last-name': {'recall': 0.9879518072289156, 'accuracy': 0.9785202863961814, 'f1_score': 0.9891435464414957, 'precision': 0.9903381642512077}, 'patient.last-name': {'recall': 0.9879518072289156, 'accuracy': 0.9785202863961814, 'f1_score': 0.9891435464414957, 'precision': 0.9903381642512077}, 'patient-first-name': {'recall': 0.9927652733118971, 'accuracy': 0.9872102318145484, 'f1_score': 0.9935639581657282, 'precision': 0.9943639291465378}, 'patient.first-name': {'recall': 0.9911575562700965, 'accuracy': 0.9848242811501597, 'f1_score': 0.9923541247484909, 'precision': 0.9935535858178888}, 'patient-middle-name': {'recall': 0.9182692307692307, 'accuracy': 0.9641434262948207, 'f1_score': 0.8946135831381734, 'precision': 0.8721461187214612}, 'patient.middle-name': {'recall': 0.9519230769230769, 'accuracy': 0.9776, 'f1_score': 0.9339622641509433, 'precision': 0.9166666666666666}, 'other-insurance-name-1': {'recall': 0.7476190476190476, 'accuracy': 0.8555900621118012, 'f1_score': 0.7714987714987716, 'precision': 0.7969543147208121}, 'other-insurance-name-2': {'recall': 1.0, 'accuracy': 0.9975903614457832, 'f1_score': 0.4, 'precision': 0.25}, 'social-security-number': {'recall': 0.9210526315789473, 'accuracy': 0.9847634322373697, 'f1_score': 0.7865168539325842, 'precision': 0.6862745098039216}, 'other-insurance-number-1': {'recall': 0.8333333333333334, 'accuracy': 0.9074221867517956, 'f1_score': 0.857843137254902, 'precision': 0.8838383838383839}, 'other-insurance-number-2': {'recall': 1.0, 'accuracy': 0.9975903614457832, 'f1_score': 0.4, 'precision': 0.25}, 'medicaid-insurance-number': {'recall': 0.8899297423887588, 'accuracy': 0.915481832543444, 'f1_score': 0.8765859284890427, 'precision': 0.8636363636363636}, 'medicare-insurance-number': {'recall': 0.9224137931034483, 'accuracy': 0.9459888800635425, 'f1_score': 0.9042253521126761, 'precision': 0.8867403314917127}}, 'metadata': {'clearml_details': {'hf_model_id': '314e/dexit-aitest-vlm_qwen3_6-entity-integration', 'clearml_task_id': 'aca31aa9c3624759b08e0c983307a86e', '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'], 'new_modelversion_tag': 'v6.0.0', 'base_modelversion_tag': 'v4.0.0'}, 'hyperparameters': {'DATASET_PARAMS': {'DATASET__EVAL_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/eval.json', 'DATASET__TEST_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/test.json', 'DATASET__TRAIN_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/train.json', 'DATASET__MISCELLANEOUS_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/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': 'v4.0.0', 'HF_BASE_MODEL_ID': 'Qwen/Qwen3.6-27B', 'IMAGE_PATCH_SIZE': 16, 'THRESHOLD_OFFSET': 0.05, 'TRAIN_OOTB_MODEL': True, 'NEW_MODELVERSIONTAG': 'v6.0.0'}, 'MODEL_HYPERPARAMETERS': {'RANK': 256, 'ALPHA': 512, 'TRAIN_EPOCHS': 4, 'EVAL_BATCH_SIZE': 1, 'GRAD_ACCUM_STEPS': 4, 'TRAIN_BATCH_SIZE': 8, 'INFERENCE_BATCH_SIZE': 10}}, 'workflow_details': {'temporal_workflow_id': 'local-model-retraining-entity-fde59196', 'skypilot_cluster_name': 'dexit-aitest-skypilot-entity-1787487611-069422', 'temporal_workflow_run_id': '01a02e90-340f-7c62-a77a-e4d517ae68fe'}, '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': 0.8, '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': 0.7, 'mid_precision_bucket_corrected_sample_rate': 0.7, 'high_precision_bucket_corrected_sample_rate': 0.8, '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': 256, 'alpha': 512, 'train_epochs': 4, 'grad_accum_steps': 4, 'train_batch_size': 8}, '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-
|
| 20 |
-
2026-
|
| 21 |
-
2026-
|
| 22 |
-
2026-
|
| 23 |
-
2026-
|
| 24 |
-
2026-
|
| 25 |
-
2026-
|
| 26 |
-
2026-
|
| 27 |
-
2026-
|
| 28 |
Dataset Split Statistics:
|
| 29 |
-
2026-
|
| 30 |
-
2026-
|
| 31 |
-
2026-
|
| 32 |
-
2026-
|
| 33 |
-
2026-
|
| 34 |
-
2026-
|
| 35 |
-
2026-
|
| 36 |
-
2026-
|
| 37 |
-
2026-
|
| 38 |
-
2026-
|
| 39 |
-
2026-
|
| 40 |
-
2026-
|
| 41 |
-
2026-
|
| 42 |
-
2026-
|
| 43 |
-
2026-
|
| 44 |
-
2026-08-24 03:51:10.696 | INFO | app.tasks.entity.vlm.model:train_model:630 - training complete: TrainOutput(global_step=528, training_loss=0.17339354160834441, metrics={'train_runtime': 54443.921, 'train_samples_per_second': 0.31, 'train_steps_per_second': 0.01, 'total_flos': 6.503342811375823e+18, 'train_loss': 0.17339354160834441, 'epoch': 3.969924812030075})
|
|
|
|
| 1 |
+
2026-09-28 11:14:54.732 | INFO | app.tasks.entity.vlm.dataset:create:710 - Using pre-split dataset mode
|
| 2 |
+
2026-09-28 11:14:54.752 | INFO | app.tasks.entity.vlm.dataset:_download_current_splits:1464 - Downloading train dataset from s3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/train.json
|
| 3 |
+
2026-09-28 11:14:55.394 | INFO | app.tasks.entity.vlm.dataset:_download_split_documents:1309 - Processing %s %s/%s with %d documents
|
| 4 |
+
2026-09-28 11:15:55.722 | INFO | app.tasks.entity.vlm.dataset:_download_current_splits:1464 - Downloading val dataset from s3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/eval.json
|
| 5 |
+
2026-09-28 11:15:56.092 | INFO | app.tasks.entity.vlm.dataset:_download_split_documents:1309 - Processing %s %s/%s with %d documents
|
| 6 |
+
2026-09-28 11:16:02.868 | INFO | app.tasks.entity.vlm.dataset:_download_current_splits:1464 - Downloading test dataset from s3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/test.json
|
| 7 |
+
2026-09-28 11:16:03.807 | INFO | app.tasks.entity.vlm.dataset:_download_split_documents:1309 - Processing %s %s/%s with %d documents
|
| 8 |
+
2026-09-28 11:16:25.849 | INFO | app.tasks.entity.vlm.dataset:_download_miscellaneous:1512 - Downloading miscellaneous data from s3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/miscellaneous.json
|
| 9 |
+
2026-09-28 11:16:26.205 | INFO | app.tasks.entity.vlm.dataset:_download_previous_datasets:1418 - Found 0 previous dataset(s) to consolidate
|
| 10 |
+
2026-09-28 11:16:26.206 | INFO | app.tasks.entity.vlm.dataset:download_presplit_datasets:1569 - Successfully downloaded all datasets to /home/ubuntu/dataset
|
| 11 |
+
2026-09-28 11:16:49.625 | INFO | app.tasks.entity.vlm.dataset:remove_null_files:636 - Removed 2 files with null values
|
| 12 |
+
2026-09-28 11:16:52.265 | INFO | app.tasks.entity.vlm.reports:get_distribution:1370 - Original number of ground truth files 6058
|
| 13 |
+
2026-09-28 11:16:58.009 | INFO | app.tasks.entity.vlm.reports:get_distribution:1385 - After removing empty files 6058
|
| 14 |
+
2026-09-28 11:16:58.245 | INFO | app.tasks.entity.vlm.reports:get_entity_distribution:1477 - Creating entity distribution for 6058 files
|
| 15 |
+
2026-09-28 11:17:02.842 | DEBUG | app.commonmlops:get_oauth_token:744 - OAuth token request status: 200
|
| 16 |
+
2026-09-28 11:17:03.177 | DEBUG | app.commonmlops:get_training_job_queue:801 - Get training job queue status code: 200, api_url: https://aitest.api.dexit.tech/api/v1/mlops/trainingjobqueue/06a665f8-ebd0-7481-8000-83304d751ace
|
| 17 |
+
2026-09-28 11:17:03.402 | DEBUG | app.commonmlops:get_oauth_token:744 - OAuth token request status: 200
|
| 18 |
+
2026-09-28 11:17:03.404 | DEBUG | app.commonmlops:update_training_job_queue:847 - Updating training job queue with merged payload: {'id': '06a665f8-ebd0-7481-8000-83304d751ace', 'modeltype': 'entity', 'modelname': 'vlm_qwen3_6', 'jobtype': 'feedback', 'basemodelversionid': '019f0d56-3844-7c0a-8fab-4aa6a6d1f12e', 'datasetid': '06a665f5-06bf-7f15-8000-acbbe709e051', 'status': 'triggered', 'createddate': '2026-07-26T19:27:10.738422Z', 'createdby': '00000000-0000-0000-0000-000000000000', 'startdate': '2026-09-28T11:14:24.598208Z', 'enddate': None, 'accuracyreport': {'overall': {'recall': 0.9632857303497132, 'f1_score': 0.9643972868762488, 'precision': 0.9655114116652578}, 'patient': {'recall': 0.9570468593654881, 'accuracy': 0.965850180851059, 'f1_score': 0.9578867442511313, 'precision': 0.9588553005522813}, 'facility': {'recall': 0.9681215596546779, 'accuracy': 0.9468811825459762, 'f1_score': 0.9706030656585861, 'precision': 0.9731011770220469}, 'patient-dob': {'recall': 0.9906303236797275, 'accuracy': 0.982484076433121, 'f1_score': 0.9906303236797275, 'precision': 0.9906303236797275}, 'patient-sex': {'recall': 0.9991423670668954, 'accuracy': 0.9975903614457832, 'f1_score': 0.9987141020145736, 'precision': 0.998286203941731}, 'patient-zip': {'recall': 0.9623762376237623, 'accuracy': 0.983159582999198, 'f1_score': 0.9788519637462235, 'precision': 0.9959016393442623}, 'patient.dob': {'recall': 0.9821124361158433, 'accuracy': 0.9706582077716098, 'f1_score': 0.9842082799829279, 'precision': 0.9863130881094953}, 'patient.sex': {'recall': 0.9991423670668954, 'accuracy': 0.9983935742971888, 'f1_score': 0.9991423670668954, 'precision': 0.9991423670668954}, 'patient.zip': {'recall': 0.9663366336633663, 'accuracy': 0.9847512038523274, 'f1_score': 0.9809045226130653, 'precision': 0.9959183673469387}, 'sample-code': {'recall': 0.9727891156462585, 'accuracy': 0.9529314616019818, 'f1_score': 0.9723166585721223, 'precision': 0.9718446601941747}, 'facility-zip': {'recall': 0.9813717188823031, 'accuracy': 0.9768370607028753, 'f1_score': 0.9876438005965062, 'precision': 0.9939965694682675}, 'facility.zip': {'recall': 0.9847586790855207, 'accuracy': 0.9808, 'f1_score': 0.9897872340425531, 'precision': 0.9948674080410608}, 'patient-city': {'recall': 0.9776876267748479, 'accuracy': 0.9864108713029577, 'f1_score': 0.9826707441386341, 'precision': 0.9877049180327869}, 'patient.city': {'recall': 0.9817444219066938, 'accuracy': 0.988, 'f1_score': 0.9847405900305187, 'precision': 0.9877551020408163}, 'phone-number': {'recall': 0.9856115107913669, 'accuracy': 0.9871794871794872, 'f1_score': 0.9716312056737588, 'precision': 0.958041958041958}, 'provider-npi': {'recall': 1.0, 'accuracy': 0.9991546914623838, 'f1_score': 0.9995147986414362, 'precision': 0.9990300678952473}, 'facility-city': {'recall': 0.9948761742100769, 'accuracy': 0.9935846030473136, 'f1_score': 0.9965782720273738, 'precision': 0.998286203941731}, 'facility-name': {'recall': 0.9709649871904356, 'accuracy': 0.9490595611285266, 'f1_score': 0.9722103463018384, 'precision': 0.973458904109589}, 'facility.city': {'recall': 0.9965841161400513, 'accuracy': 0.9967871485943776, 'f1_score': 0.998289136013687, 'precision': 1.0}, 'facility.name': {'recall': 0.9624252775405636, 'accuracy': 0.9339035769828927, 'f1_score': 0.9636596836254809, 'precision': 0.9648972602739726}, 'patient-state': {'recall': 0.8492366412213741, 'accuracy': 0.8814589665653495, 'f1_score': 0.8508604206500956, 'precision': 0.8524904214559387}, 'patient.state': {'recall': 0.8530534351145038, 'accuracy': 0.8843226788432268, 'f1_score': 0.8546845124282982, 'precision': 0.8563218390804598}, 'facility-state': {'recall': 0.9182282793867121, 'accuracy': 0.8605697151424287, 'f1_score': 0.9205807002561913, 'precision': 0.922945205479452}, 'facility.state': {'recall': 0.9335604770017035, 'accuracy': 0.8867781155015197, 'f1_score': 0.936351986330628, 'precision': 0.9391602399314481}, 'collection-date': {'recall': 0.9309734513274336, 'accuracy': 0.9377593360995851, 'f1_score': 0.9334516415261758, 'precision': 0.9359430604982206}, 'patient-address': {'recall': 0.9, 'accuracy': 0.9271317829457364, 'f1_score': 0.903688524590164, 'precision': 0.9074074074074074}, 'patient.address': {'recall': 0.9, 'accuracy': 0.9255813953488372, 'f1_score': 0.901840490797546, 'precision': 0.9036885245901639}, 'accession-number': {'recall': 0.9967948717948718, 'accuracy': 0.9991546914623838, 'f1_score': 0.9983948635634029, 'precision': 1.0}, 'facility-address': {'recall': 0.964133219470538, 'accuracy': 0.9376461418550273, 'f1_score': 0.9657827202737382, 'precision': 0.9674378748928878}, 'facility.address': {'recall': 0.9632792485055508, 'accuracy': 0.9361370716510904, 'f1_score': 0.9649272882805817, 'precision': 0.9665809768637532}, 'patient-last-name': {'recall': 0.98714859437751, 'accuracy': 0.9753968253968254, 'f1_score': 0.9875451988750501, 'precision': 0.9879421221864951}, 'patient.last-name': {'recall': 0.9879518072289156, 'accuracy': 0.9785202863961814, 'f1_score': 0.9891435464414957, 'precision': 0.9903381642512077}, 'patient-first-name': {'recall': 0.9927652733118971, 'accuracy': 0.985634477254589, 'f1_score': 0.9927652733118971, 'precision': 0.9927652733118971}, 'patient.first-name': {'recall': 0.9911575562700965, 'accuracy': 0.9848242811501597, 'f1_score': 0.9923541247484909, 'precision': 0.9935535858178888}, 'patient-middle-name': {'recall': 0.9567307692307693, 'accuracy': 0.9767628205128205, 'f1_score': 0.9320843091334894, 'precision': 0.908675799086758}, 'patient.middle-name': {'recall': 0.9519230769230769, 'accuracy': 0.9776, 'f1_score': 0.9339622641509433, 'precision': 0.9166666666666666}, 'other-insurance-name-1': {'recall': 0.8214285714285714, 'accuracy': 0.8868954758190327, 'f1_score': 0.8263473053892216, 'precision': 0.8313253012048193}, 'other-insurance-name-2': {'recall': 1.0, 'accuracy': 0.9983935742971888, 'f1_score': 0.5, 'precision': 0.3333333333333333}, 'social-security-number': {'recall': 0.8947368421052632, 'accuracy': 0.98714859437751, 'f1_score': 0.8095238095238095, 'precision': 0.7391304347826086}, 'other-insurance-number-1': {'recall': 0.9047619047619048, 'accuracy': 0.9391025641025641, 'f1_score': 0.9090909090909091, 'precision': 0.9134615384615384}, 'other-insurance-number-2': {'recall': 1.0, 'accuracy': 0.9983935742971888, 'f1_score': 0.5, 'precision': 0.3333333333333333}, 'medicaid-insurance-number': {'recall': 0.9039812646370023, 'accuracy': 0.9304897314375987, 'f1_score': 0.8976744186046511, 'precision': 0.8914549653579676}, 'medicare-insurance-number': {'recall': 0.9511494252873564, 'accuracy': 0.9784172661870504, 'f1_score': 0.9608127721335269, 'precision': 0.9706744868035191}}, 'metadata': {'clearml_details': {'hf_model_id': '314e/dexit-aitest-vlm_qwen3_6-entity-integration', 'clearml_task_id': '087ac1190c34477ab0fc94903e1797ff', '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'], 'new_modelversion_tag': 'v8.0.0', 'base_modelversion_tag': 'v1.0.0'}, 'hyperparameters': {'DATASET_PARAMS': {'DATASET__EVAL_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/eval.json', 'DATASET__TEST_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/test.json', 'DATASET__TRAIN_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/train.json', 'DATASET__MISCELLANEOUS_S3_PATH': 's3://aitest-dexit-tech/data/__mlops__/dataset/entity/06a665f5-06bf-7f15-8000-acbbe709e051/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': 'v1.0.0', 'HF_BASE_MODEL_ID': 'Qwen/Qwen3.6-27B', 'IMAGE_PATCH_SIZE': 16, 'THRESHOLD_OFFSET': 0.05, 'TRAIN_OOTB_MODEL': True, 'NEW_MODELVERSIONTAG': 'v8.0.0'}, 'MODEL_HYPERPARAMETERS': {'RANK': 256, 'ALPHA': 512, 'TRAIN_EPOCHS': 2, 'EVAL_BATCH_SIZE': 1, 'GRAD_ACCUM_STEPS': 4, 'TRAIN_BATCH_SIZE': 8, 'INFERENCE_BATCH_SIZE': 10}}, 'workflow_details': {'temporal_workflow_id': 'local-model-retraining-entity-787d0b1f', 'skypilot_cluster_name': 'dexit-aitest-skypilot-entity-1790593503-949662', 'temporal_workflow_run_id': '01a0e7b0-5b96-7285-a7c6-103c9d3dd84f'}, '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': 0.8, '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': 0.7, 'mid_precision_bucket_corrected_sample_rate': 0.7, 'high_precision_bucket_corrected_sample_rate': 0.8, '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': 256, 'alpha': 512, 'train_epochs': 2, 'grad_accum_steps': 4, 'train_batch_size': 8, 'inference_batch_size': 10}, '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 |
+
2026-09-28 11:17:03.724 | DEBUG | app.commonmlops:update_training_job_queue:850 - Update training job queue status code: 200, api_url: https://aitest.api.dexit.tech/api/v1/mlops/trainingjobqueue/06a665f8-ebd0-7481-8000-83304d751ace
|
| 20 |
+
2026-09-28 11:17:03.725 | SUCCESS | app.commonmlops:update_trained_entities:889 - Updated trained_entities on training job queue
|
| 21 |
+
2026-09-28 11:17:04.171 | INFO | app.tasks.entity.vlm.reports:upload_initial_artifacts:1546 - Uploaded intial artifacts to ClearML
|
| 22 |
+
2026-09-28 11:17:04.172 | INFO | __main__:_run_training_phase:635 - Moving into standard training loop
|
| 23 |
+
2026-09-28 11:17:04.173 | INFO | __main__:setup_directories:210 - Loading pre-split dataset statistics
|
| 24 |
+
2026-09-28 11:17:06.164 | INFO | __main__:load_presplit_statistics:187 - Found 4250 training samples
|
| 25 |
+
2026-09-28 11:17:06.731 | INFO | __main__:load_presplit_statistics:189 - Found 1245 test samples
|
| 26 |
+
2026-09-28 11:17:07.005 | INFO | __main__:load_presplit_statistics:191 - Found 563 validation samples
|
| 27 |
+
2026-09-28 11:17:07.006 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:835 -
|
| 28 |
Dataset Split Statistics:
|
| 29 |
+
2026-09-28 11:17:07.007 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:836 - Total samples: 6058
|
| 30 |
+
2026-09-28 11:17:07.007 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:838 - Train set: 4250 (70.2%)
|
| 31 |
+
2026-09-28 11:17:07.007 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:839 - Test set: 1245 (20.6%)
|
| 32 |
+
2026-09-28 11:17:07.008 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:840 - Validation set: 563 (9.3%)
|
| 33 |
+
2026-09-28 11:17:07.010 | INFO | app.tasks.entity.vlm.dataset:print_split_statistics:853 - Split statistics saved to /home/ubuntu/result/split_statistics.json
|
| 34 |
+
2026-09-28 11:17:07.601 | INFO | __main__:standard_training_loop:332 - Initializing model
|
| 35 |
+
2026-09-28 11:17:07.602 | INFO | __main__:initialize_model:242 - Setting up model for retraining
|
| 36 |
+
2026-09-28 11:17:07.602 | INFO | __main__:initialize_model:245 - Training from base model: Qwen/Qwen3.6-27B
|
| 37 |
+
2026-09-28 11:17:07.602 | INFO | app.tasks.entity.vlm.model:__post_init__:321 - loading model Qwen/Qwen3.6-27B for training with unsloth
|
| 38 |
+
2026-09-28 11:24:32.391 | INFO | app.tasks.entity.vlm.model:calculate_max_steps:417 - num_samples: 4250, batch_size: 8, gradient_accumulation_steps: 4, epochs: 2
|
| 39 |
+
2026-09-28 11:24:32.393 | INFO | app.tasks.entity.vlm.model:calculate_max_steps:421 - calculating max steps
|
| 40 |
+
2026-09-28 11:24:32.432 | INFO | __main__:standard_training_loop:335 - Setting up trainer
|
| 41 |
+
2026-09-28 11:24:32.432 | INFO | __main__:create_trainer:284 - Datasets: 4250 train, 563 eval samples
|
| 42 |
+
2026-09-28 11:24:32.920 | INFO | __main__:standard_training_loop:338 - Starting training
|
| 43 |
+
2026-09-28 11:24:33.104 | INFO | app.tasks.entity.vlm.model:train_model:624 - everything is set up, launching training
|
|
|
ground_truth_data.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
gt_json.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
runs/Sep28_11-24-35_191e889c7694/events.out.tfevents.1790594675.191e889c7694.10027.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:31f09c75006eeeaa0403ad17dc4386644eee5d49a84f6a4a02b9fdde110e2cc7
|
| 3 |
+
size 12463
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5905
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cea301ee295c8c68b7bebf9acc1c507cf6269e3eec8c86f27081392ad41371ab
|
| 3 |
size 5905
|