Instructions to use WhiteRoomProdigy/amicus-ner-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WhiteRoomProdigy/amicus-ner-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="WhiteRoomProdigy/amicus-ner-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("WhiteRoomProdigy/amicus-ner-v1") model = AutoModelForTokenClassification.from_pretrained("WhiteRoomProdigy/amicus-ner-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_global_step": 7, | |
| "best_metric": 0.0, | |
| "best_model_checkpoint": "/content/drive/MyDrive/amicus_ner/data/models/amicus-ner-v1/checkpoint-7", | |
| "epoch": 3.0, | |
| "eval_steps": 500, | |
| "global_step": 21, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_f1": 0.0, | |
| "eval_loss": 0.4407300055027008, | |
| "eval_runtime": 0.2365, | |
| "eval_samples_per_second": 59.199, | |
| "eval_steps_per_second": 4.229, | |
| "step": 7 | |
| }, | |
| { | |
| "epoch": 1.4285714285714286, | |
| "grad_norm": 0.4826352298259735, | |
| "learning_rate": 3.7142857142857143e-05, | |
| "loss": 0.9833, | |
| "step": 10 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_f1": 0.0, | |
| "eval_loss": 0.37621578574180603, | |
| "eval_runtime": 0.2149, | |
| "eval_samples_per_second": 65.147, | |
| "eval_steps_per_second": 4.653, | |
| "step": 14 | |
| }, | |
| { | |
| "epoch": 2.857142857142857, | |
| "grad_norm": 1.2109462022781372, | |
| "learning_rate": 2.2857142857142858e-05, | |
| "loss": 0.3131, | |
| "step": 20 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_f1": 0.0, | |
| "eval_loss": 0.29709503054618835, | |
| "eval_runtime": 0.2378, | |
| "eval_samples_per_second": 58.869, | |
| "eval_steps_per_second": 4.205, | |
| "step": 21 | |
| } | |
| ], | |
| "logging_steps": 10, | |
| "max_steps": 35, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 5, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": false | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 21951904149504.0, | |
| "train_batch_size": 8, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |