Instructions to use pankajrudra/MediBool-banglabert-Context_Aware with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pankajrudra/MediBool-banglabert-Context_Aware with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pankajrudra/MediBool-banglabert-Context_Aware")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pankajrudra/MediBool-banglabert-Context_Aware") model = AutoModelForSequenceClassification.from_pretrained("pankajrudra/MediBool-banglabert-Context_Aware", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_global_step": 1500, | |
| "best_metric": 0.9925512104283054, | |
| "best_model_checkpoint": "./res_Context_Aware_banglabert/checkpoint-1500", | |
| "epoch": 3.303964757709251, | |
| "eval_steps": 250, | |
| "global_step": 1500, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.11013215859030837, | |
| "grad_norm": 25.462419509887695, | |
| "learning_rate": 4.9e-05, | |
| "loss": 1.1988423156738282, | |
| "step": 50 | |
| }, | |
| { | |
| "epoch": 0.22026431718061673, | |
| "grad_norm": 6.222968101501465, | |
| "learning_rate": 4.88963963963964e-05, | |
| "loss": 0.4401987075805664, | |
| "step": 100 | |
| }, | |
| { | |
| "epoch": 0.3303964757709251, | |
| "grad_norm": 4.529721736907959, | |
| "learning_rate": 4.7770270270270274e-05, | |
| "loss": 0.22516624450683595, | |
| "step": 150 | |
| }, | |
| { | |
| "epoch": 0.44052863436123346, | |
| "grad_norm": 14.54383659362793, | |
| "learning_rate": 4.664414414414415e-05, | |
| "loss": 0.19179162979125977, | |
| "step": 200 | |
| }, | |
| { | |
| "epoch": 0.5506607929515418, | |
| "grad_norm": 2.3169732093811035, | |
| "learning_rate": 4.551801801801802e-05, | |
| "loss": 0.18978879928588868, | |
| "step": 250 | |
| }, | |
| { | |
| "epoch": 0.5506607929515418, | |
| "eval_accuracy": 0.9826194909993793, | |
| "eval_f1": 0.98261752029853, | |
| "eval_loss": 0.12076283246278763, | |
| "eval_runtime": 15.2108, | |
| "eval_samples_per_second": 105.912, | |
| "eval_steps_per_second": 0.855, | |
| "step": 250 | |
| }, | |
| { | |
| "epoch": 0.6607929515418502, | |
| "grad_norm": 0.8863422274589539, | |
| "learning_rate": 4.439189189189189e-05, | |
| "loss": 0.13721893310546876, | |
| "step": 300 | |
| }, | |
| { | |
| "epoch": 0.7709251101321586, | |
| "grad_norm": 0.7998637557029724, | |
| "learning_rate": 4.326576576576577e-05, | |
| "loss": 0.12599869728088378, | |
| "step": 350 | |
| }, | |
| { | |
| "epoch": 0.8810572687224669, | |
| "grad_norm": 7.37066650390625, | |
| "learning_rate": 4.2139639639639646e-05, | |
| "loss": 0.11998005867004395, | |
| "step": 400 | |
| }, | |
| { | |
| "epoch": 0.9911894273127754, | |
| "grad_norm": 0.12422619014978409, | |
| "learning_rate": 4.101351351351351e-05, | |
| "loss": 0.1296429443359375, | |
| "step": 450 | |
| }, | |
| { | |
| "epoch": 1.1013215859030836, | |
| "grad_norm": 0.6420861482620239, | |
| "learning_rate": 3.9887387387387386e-05, | |
| "loss": 0.06252753257751464, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 1.1013215859030836, | |
| "eval_accuracy": 0.9844816883923029, | |
| "eval_f1": 0.9844755809919153, | |
| "eval_loss": 0.13376149535179138, | |
| "eval_runtime": 15.1806, | |
| "eval_samples_per_second": 106.122, | |
| "eval_steps_per_second": 0.856, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 1.2114537444933922, | |
| "grad_norm": 1.574205756187439, | |
| "learning_rate": 3.876126126126126e-05, | |
| "loss": 0.091258544921875, | |
| "step": 550 | |
| }, | |
| { | |
| "epoch": 1.3215859030837005, | |
| "grad_norm": 0.36328908801078796, | |
| "learning_rate": 3.763513513513513e-05, | |
| "loss": 0.06470813274383545, | |
| "step": 600 | |
| }, | |
| { | |
| "epoch": 1.4317180616740088, | |
| "grad_norm": 3.5949654579162598, | |
| "learning_rate": 3.650900900900901e-05, | |
| "loss": 0.07118824481964112, | |
| "step": 650 | |
| }, | |
| { | |
| "epoch": 1.5418502202643172, | |
| "grad_norm": 18.810028076171875, | |
| "learning_rate": 3.5382882882882885e-05, | |
| "loss": 0.04942235469818115, | |
| "step": 700 | |
| }, | |
| { | |
| "epoch": 1.6519823788546255, | |
| "grad_norm": 1.473706603050232, | |
| "learning_rate": 3.425675675675676e-05, | |
| "loss": 0.06424750804901123, | |
| "step": 750 | |
| }, | |
| { | |
| "epoch": 1.6519823788546255, | |
| "eval_accuracy": 0.9875853507138423, | |
| "eval_f1": 0.9875866907189155, | |
| "eval_loss": 0.0764322504401207, | |
| "eval_runtime": 15.2295, | |
| "eval_samples_per_second": 105.782, | |
| "eval_steps_per_second": 0.854, | |
| "step": 750 | |
| }, | |
| { | |
| "epoch": 1.7621145374449338, | |
| "grad_norm": 2.166792869567871, | |
| "learning_rate": 3.313063063063063e-05, | |
| "loss": 0.05474145412445068, | |
| "step": 800 | |
| }, | |
| { | |
| "epoch": 1.8722466960352424, | |
| "grad_norm": 10.277437210083008, | |
| "learning_rate": 3.2004504504504505e-05, | |
| "loss": 0.06158576011657715, | |
| "step": 850 | |
| }, | |
| { | |
| "epoch": 1.9823788546255505, | |
| "grad_norm": 16.316560745239258, | |
| "learning_rate": 3.087837837837838e-05, | |
| "loss": 0.03567867040634155, | |
| "step": 900 | |
| }, | |
| { | |
| "epoch": 2.092511013215859, | |
| "grad_norm": 0.021065015345811844, | |
| "learning_rate": 2.9752252252252255e-05, | |
| "loss": 0.017343584299087524, | |
| "step": 950 | |
| }, | |
| { | |
| "epoch": 2.202643171806167, | |
| "grad_norm": 6.482810974121094, | |
| "learning_rate": 2.8626126126126128e-05, | |
| "loss": 0.03294461965560913, | |
| "step": 1000 | |
| }, | |
| { | |
| "epoch": 2.202643171806167, | |
| "eval_accuracy": 0.9894475481067659, | |
| "eval_f1": 0.9894451302143361, | |
| "eval_loss": 0.10190387815237045, | |
| "eval_runtime": 15.171, | |
| "eval_samples_per_second": 106.19, | |
| "eval_steps_per_second": 0.857, | |
| "step": 1000 | |
| }, | |
| { | |
| "epoch": 2.3127753303964758, | |
| "grad_norm": 0.015216778963804245, | |
| "learning_rate": 2.7500000000000004e-05, | |
| "loss": 0.034067885875701906, | |
| "step": 1050 | |
| }, | |
| { | |
| "epoch": 2.4229074889867843, | |
| "grad_norm": 0.2629091143608093, | |
| "learning_rate": 2.6373873873873878e-05, | |
| "loss": 0.03687331676483154, | |
| "step": 1100 | |
| }, | |
| { | |
| "epoch": 2.5330396475770924, | |
| "grad_norm": 0.015911059454083443, | |
| "learning_rate": 2.5247747747747747e-05, | |
| "loss": 0.03307219266891479, | |
| "step": 1150 | |
| }, | |
| { | |
| "epoch": 2.643171806167401, | |
| "grad_norm": 0.5511289238929749, | |
| "learning_rate": 2.4121621621621624e-05, | |
| "loss": 0.0193754243850708, | |
| "step": 1200 | |
| }, | |
| { | |
| "epoch": 2.753303964757709, | |
| "grad_norm": 1.5788966417312622, | |
| "learning_rate": 2.2995495495495497e-05, | |
| "loss": 0.019393556118011475, | |
| "step": 1250 | |
| }, | |
| { | |
| "epoch": 2.753303964757709, | |
| "eval_accuracy": 0.9900682805710739, | |
| "eval_f1": 0.990065222973868, | |
| "eval_loss": 0.11733845621347427, | |
| "eval_runtime": 15.2803, | |
| "eval_samples_per_second": 105.43, | |
| "eval_steps_per_second": 0.851, | |
| "step": 1250 | |
| }, | |
| { | |
| "epoch": 2.8634361233480177, | |
| "grad_norm": 0.007190010976046324, | |
| "learning_rate": 2.186936936936937e-05, | |
| "loss": 0.012289742231369019, | |
| "step": 1300 | |
| }, | |
| { | |
| "epoch": 2.9735682819383262, | |
| "grad_norm": 0.007357372902333736, | |
| "learning_rate": 2.0743243243243243e-05, | |
| "loss": 0.016530017852783203, | |
| "step": 1350 | |
| }, | |
| { | |
| "epoch": 3.0837004405286343, | |
| "grad_norm": 0.02660430781543255, | |
| "learning_rate": 1.9617117117117117e-05, | |
| "loss": 0.01394943118095398, | |
| "step": 1400 | |
| }, | |
| { | |
| "epoch": 3.193832599118943, | |
| "grad_norm": 0.007937883026897907, | |
| "learning_rate": 1.8490990990990993e-05, | |
| "loss": 0.010230660438537598, | |
| "step": 1450 | |
| }, | |
| { | |
| "epoch": 3.303964757709251, | |
| "grad_norm": 0.009734545834362507, | |
| "learning_rate": 1.7364864864864866e-05, | |
| "loss": 0.023434817790985107, | |
| "step": 1500 | |
| }, | |
| { | |
| "epoch": 3.303964757709251, | |
| "eval_accuracy": 0.9925512104283054, | |
| "eval_f1": 0.9925496876355572, | |
| "eval_loss": 0.09795740991830826, | |
| "eval_runtime": 15.1562, | |
| "eval_samples_per_second": 106.293, | |
| "eval_steps_per_second": 0.858, | |
| "step": 1500 | |
| } | |
| ], | |
| "logging_steps": 50, | |
| "max_steps": 2270, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 5, | |
| "save_steps": 250, | |
| "stateful_callbacks": { | |
| "EarlyStoppingCallback": { | |
| "args": { | |
| "early_stopping_patience": 3, | |
| "early_stopping_threshold": 0.0 | |
| }, | |
| "attributes": { | |
| "early_stopping_patience_counter": 0 | |
| } | |
| }, | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 1.260525599571456e+16, | |
| "train_batch_size": 64, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |