Instructions to use whitedevil0089devil/roberta_base_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whitedevil0089devil/roberta_base_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whitedevil0089devil/roberta_base_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whitedevil0089devil/roberta_base_1") model = AutoModelForSequenceClassification.from_pretrained("whitedevil0089devil/roberta_base_1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_global_step": 200, | |
| "best_metric": 0.9943728018757327, | |
| "best_model_checkpoint": "/content/drive/MyDrive/model/roberta_model/checkpoint-200", | |
| "epoch": 0.18757327080890973, | |
| "eval_steps": 200, | |
| "global_step": 800, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.00023446658851113716, | |
| "grad_norm": 7.900483131408691, | |
| "learning_rate": 0.0, | |
| "loss": 1.2285, | |
| "step": 1 | |
| }, | |
| { | |
| "epoch": 0.023446658851113716, | |
| "grad_norm": 2.4035584926605225, | |
| "learning_rate": 2.9015240328253227e-06, | |
| "loss": 0.9217, | |
| "step": 100 | |
| }, | |
| { | |
| "epoch": 0.04689331770222743, | |
| "grad_norm": 0.31396016478538513, | |
| "learning_rate": 5.832356389214537e-06, | |
| "loss": 0.073, | |
| "step": 200 | |
| }, | |
| { | |
| "epoch": 0.04689331770222743, | |
| "eval_accuracy": 0.9943728018757327, | |
| "eval_f1_macro": 0.24929461556548319, | |
| "eval_f1_weighted": 0.9915671414895327, | |
| "eval_loss": 0.04064385965466499, | |
| "eval_runtime": 57.486, | |
| "eval_samples_per_second": 148.384, | |
| "eval_steps_per_second": 9.289, | |
| "step": 200 | |
| }, | |
| { | |
| "epoch": 0.07033997655334115, | |
| "grad_norm": 0.14905625581741333, | |
| "learning_rate": 8.763188745603752e-06, | |
| "loss": 0.0474, | |
| "step": 300 | |
| }, | |
| { | |
| "epoch": 0.09378663540445487, | |
| "grad_norm": 0.08281561732292175, | |
| "learning_rate": 1.1694021101992966e-05, | |
| "loss": 0.0334, | |
| "step": 400 | |
| }, | |
| { | |
| "epoch": 0.09378663540445487, | |
| "eval_accuracy": 0.9943728018757327, | |
| "eval_f1_macro": 0.24929461556548319, | |
| "eval_f1_weighted": 0.9915671414895327, | |
| "eval_loss": 0.04262762889266014, | |
| "eval_runtime": 54.8606, | |
| "eval_samples_per_second": 155.485, | |
| "eval_steps_per_second": 9.734, | |
| "step": 400 | |
| }, | |
| { | |
| "epoch": 0.11723329425556858, | |
| "grad_norm": 0.04056438058614731, | |
| "learning_rate": 1.4624853458382182e-05, | |
| "loss": 0.04, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 0.1406799531066823, | |
| "grad_norm": 0.04737967997789383, | |
| "learning_rate": 1.7555685814771398e-05, | |
| "loss": 0.0502, | |
| "step": 600 | |
| }, | |
| { | |
| "epoch": 0.1406799531066823, | |
| "eval_accuracy": 0.9943728018757327, | |
| "eval_f1_macro": 0.24929461556548319, | |
| "eval_f1_weighted": 0.9915671414895327, | |
| "eval_loss": 0.04288283362984657, | |
| "eval_runtime": 54.7704, | |
| "eval_samples_per_second": 155.741, | |
| "eval_steps_per_second": 9.75, | |
| "step": 600 | |
| }, | |
| { | |
| "epoch": 0.16412661195779601, | |
| "grad_norm": 0.14134405553340912, | |
| "learning_rate": 2.048651817116061e-05, | |
| "loss": 0.0605, | |
| "step": 700 | |
| }, | |
| { | |
| "epoch": 0.18757327080890973, | |
| "grad_norm": 0.11066514253616333, | |
| "learning_rate": 2.3417350527549826e-05, | |
| "loss": 0.0325, | |
| "step": 800 | |
| }, | |
| { | |
| "epoch": 0.18757327080890973, | |
| "eval_accuracy": 0.9943728018757327, | |
| "eval_f1_macro": 0.24929461556548319, | |
| "eval_f1_weighted": 0.9915671414895327, | |
| "eval_loss": 0.04036899656057358, | |
| "eval_runtime": 54.8996, | |
| "eval_samples_per_second": 155.375, | |
| "eval_steps_per_second": 9.727, | |
| "step": 800 | |
| } | |
| ], | |
| "logging_steps": 100, | |
| "max_steps": 17060, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 4, | |
| "save_steps": 200, | |
| "stateful_callbacks": { | |
| "EarlyStoppingCallback": { | |
| "args": { | |
| "early_stopping_patience": 3, | |
| "early_stopping_threshold": 0.001 | |
| }, | |
| "attributes": { | |
| "early_stopping_patience_counter": 3 | |
| } | |
| }, | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 2525934167654400.0, | |
| "train_batch_size": 16, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |