Instructions to use jmmr-8282/email with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jmmr-8282/email with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jmmr-8282/email")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jmmr-8282/email") model = AutoModelForSequenceClassification.from_pretrained("jmmr-8282/email") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_global_step": 392, | |
| "best_metric": 1.9849951267242432, | |
| "best_model_checkpoint": "./bert-resume/checkpoint-392", | |
| "epoch": 3.0, | |
| "eval_steps": 500, | |
| "global_step": 588, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_loss": 2.013901472091675, | |
| "eval_runtime": 32.6312, | |
| "eval_samples_per_second": 53.905, | |
| "eval_steps_per_second": 1.686, | |
| "step": 196 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_loss": 1.9849951267242432, | |
| "eval_runtime": 32.6699, | |
| "eval_samples_per_second": 53.842, | |
| "eval_steps_per_second": 1.684, | |
| "step": 392 | |
| }, | |
| { | |
| "epoch": 2.5510204081632653, | |
| "grad_norm": 7.228590965270996, | |
| "learning_rate": 1.7454081632653063e-05, | |
| "loss": 1.8102947998046874, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_loss": 2.102543830871582, | |
| "eval_runtime": 33.1614, | |
| "eval_samples_per_second": 53.044, | |
| "eval_steps_per_second": 1.659, | |
| "step": 588 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 3920, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 20, | |
| "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": 4926272520121344.0, | |
| "train_batch_size": 32, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |