Instructions to use DerivedFunction01/twitter-roberta-base-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DerivedFunction01/twitter-roberta-base-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="DerivedFunction01/twitter-roberta-base-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("DerivedFunction01/twitter-roberta-base-sentiment") model = AutoModelForTokenClassification.from_pretrained("DerivedFunction01/twitter-roberta-base-sentiment") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_global_step": 7000, | |
| "best_metric": 0.7255222279017829, | |
| "best_model_checkpoint": "twitter-roberta-base-sentiment/checkpoint-7000", | |
| "epoch": 2.0, | |
| "eval_steps": 1000, | |
| "global_step": 7500, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.13333333333333333, | |
| "grad_norm": 20.965015411376953, | |
| "learning_rate": 4.667333333333333e-05, | |
| "loss": 1.1819219970703125, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 0.26666666666666666, | |
| "grad_norm": 11.917593955993652, | |
| "learning_rate": 4.334e-05, | |
| "loss": 0.9337052612304687, | |
| "step": 1000 | |
| }, | |
| { | |
| "epoch": 0.26666666666666666, | |
| "eval_accuracy": 0.6273213164100924, | |
| "eval_loss": 0.8398480415344238, | |
| "eval_macro_f1": 0.6322141639272949, | |
| "eval_macro_precision": 0.6576877598252542, | |
| "eval_macro_recall": 0.6722547096342347, | |
| "eval_runtime": 2.6744, | |
| "eval_samples_per_second": 747.836, | |
| "eval_steps_per_second": 93.479, | |
| "step": 1000 | |
| }, | |
| { | |
| "epoch": 0.4, | |
| "grad_norm": 23.177780151367188, | |
| "learning_rate": 4.000666666666667e-05, | |
| "loss": 0.8868782958984375, | |
| "step": 1500 | |
| }, | |
| { | |
| "epoch": 0.5333333333333333, | |
| "grad_norm": 17.591394424438477, | |
| "learning_rate": 3.667333333333334e-05, | |
| "loss": 0.8100706787109375, | |
| "step": 2000 | |
| }, | |
| { | |
| "epoch": 0.5333333333333333, | |
| "eval_accuracy": 0.6780436354155557, | |
| "eval_loss": 0.7525765299797058, | |
| "eval_macro_f1": 0.6850892519024188, | |
| "eval_macro_precision": 0.6598085660723552, | |
| "eval_macro_recall": 0.7405740499588241, | |
| "eval_runtime": 2.8793, | |
| "eval_samples_per_second": 694.617, | |
| "eval_steps_per_second": 86.827, | |
| "step": 2000 | |
| }, | |
| { | |
| "epoch": 0.6666666666666666, | |
| "grad_norm": 6.08801794052124, | |
| "learning_rate": 3.3339999999999996e-05, | |
| "loss": 0.794907470703125, | |
| "step": 2500 | |
| }, | |
| { | |
| "epoch": 0.8, | |
| "grad_norm": 27.144378662109375, | |
| "learning_rate": 3.0006666666666665e-05, | |
| "loss": 0.7096878051757812, | |
| "step": 3000 | |
| }, | |
| { | |
| "epoch": 0.8, | |
| "eval_accuracy": 0.7068060345338406, | |
| "eval_loss": 0.8074902296066284, | |
| "eval_macro_f1": 0.708147924027848, | |
| "eval_macro_precision": 0.6852926476250705, | |
| "eval_macro_recall": 0.7515385913092318, | |
| "eval_runtime": 2.799, | |
| "eval_samples_per_second": 714.547, | |
| "eval_steps_per_second": 89.318, | |
| "step": 3000 | |
| }, | |
| { | |
| "epoch": 0.9333333333333333, | |
| "grad_norm": 7.97494649887085, | |
| "learning_rate": 2.6673333333333334e-05, | |
| "loss": 0.6882199096679688, | |
| "step": 3500 | |
| }, | |
| { | |
| "epoch": 1.0666666666666667, | |
| "grad_norm": 72.2275390625, | |
| "learning_rate": 2.334e-05, | |
| "loss": 0.5513282470703125, | |
| "step": 4000 | |
| }, | |
| { | |
| "epoch": 1.0666666666666667, | |
| "eval_accuracy": 0.711297566987829, | |
| "eval_loss": 0.8309856057167053, | |
| "eval_macro_f1": 0.7134614559753025, | |
| "eval_macro_precision": 0.7006789171121683, | |
| "eval_macro_recall": 0.7316354136257511, | |
| "eval_runtime": 2.5074, | |
| "eval_samples_per_second": 797.653, | |
| "eval_steps_per_second": 99.707, | |
| "step": 4000 | |
| }, | |
| { | |
| "epoch": 1.2, | |
| "grad_norm": 15.840924263000488, | |
| "learning_rate": 2.000666666666667e-05, | |
| "loss": 0.4512594604492188, | |
| "step": 4500 | |
| }, | |
| { | |
| "epoch": 1.3333333333333333, | |
| "grad_norm": 34.06888198852539, | |
| "learning_rate": 1.6673333333333335e-05, | |
| "loss": 0.4367816467285156, | |
| "step": 5000 | |
| }, | |
| { | |
| "epoch": 1.3333333333333333, | |
| "eval_accuracy": 0.7153980161410745, | |
| "eval_loss": 0.8999603390693665, | |
| "eval_macro_f1": 0.7192265335473144, | |
| "eval_macro_precision": 0.7001483151030682, | |
| "eval_macro_recall": 0.7486556335663106, | |
| "eval_runtime": 2.9021, | |
| "eval_samples_per_second": 689.149, | |
| "eval_steps_per_second": 86.144, | |
| "step": 5000 | |
| }, | |
| { | |
| "epoch": 1.4666666666666668, | |
| "grad_norm": 22.8697566986084, | |
| "learning_rate": 1.334e-05, | |
| "loss": 0.425781982421875, | |
| "step": 5500 | |
| }, | |
| { | |
| "epoch": 1.6, | |
| "grad_norm": 35.891910552978516, | |
| "learning_rate": 1.0006666666666667e-05, | |
| "loss": 0.4083564758300781, | |
| "step": 6000 | |
| }, | |
| { | |
| "epoch": 1.6, | |
| "eval_accuracy": 0.7154217181593012, | |
| "eval_loss": 0.9041675925254822, | |
| "eval_macro_f1": 0.7193968139053373, | |
| "eval_macro_precision": 0.7035302903092748, | |
| "eval_macro_recall": 0.7413119746935019, | |
| "eval_runtime": 2.9992, | |
| "eval_samples_per_second": 666.84, | |
| "eval_steps_per_second": 83.355, | |
| "step": 6000 | |
| }, | |
| { | |
| "epoch": 1.7333333333333334, | |
| "grad_norm": 13.511373519897461, | |
| "learning_rate": 6.673333333333334e-06, | |
| "loss": 0.37453250122070314, | |
| "step": 6500 | |
| }, | |
| { | |
| "epoch": 1.8666666666666667, | |
| "grad_norm": 16.5288143157959, | |
| "learning_rate": 3.34e-06, | |
| "loss": 0.3480953063964844, | |
| "step": 7000 | |
| }, | |
| { | |
| "epoch": 1.8666666666666667, | |
| "eval_accuracy": 0.7246418032495467, | |
| "eval_loss": 0.9867857694625854, | |
| "eval_macro_f1": 0.7255222279017829, | |
| "eval_macro_precision": 0.7121027408660254, | |
| "eval_macro_recall": 0.7441490247498834, | |
| "eval_runtime": 2.8965, | |
| "eval_samples_per_second": 690.481, | |
| "eval_steps_per_second": 86.31, | |
| "step": 7000 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "grad_norm": 23.222797393798828, | |
| "learning_rate": 6.666666666666668e-09, | |
| "loss": 0.36932818603515627, | |
| "step": 7500 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.7222123463812944, | |
| "eval_loss": 0.9462353587150574, | |
| "eval_macro_f1": 0.7245504652984988, | |
| "eval_macro_precision": 0.706780387937829, | |
| "eval_macro_recall": 0.7490801491029597, | |
| "eval_runtime": 2.4998, | |
| "eval_samples_per_second": 800.072, | |
| "eval_steps_per_second": 100.009, | |
| "step": 7500 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "step": 7500, | |
| "total_flos": 4142208946914480.0, | |
| "train_loss": 0.624723681640625, | |
| "train_runtime": 564.9504, | |
| "train_samples_per_second": 212.408, | |
| "train_steps_per_second": 13.276 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 7500, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 2, | |
| "save_steps": 1000, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 4142208946914480.0, | |
| "train_batch_size": 8, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |