Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use xshubhamx/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/roberta-base") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": 0.36762215914350266, | |
| "best_model_checkpoint": "roberta-base/checkpoint-643", | |
| "epoch": 1.0, | |
| "eval_steps": 500, | |
| "global_step": 643, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 0.78, | |
| "grad_norm": 16.478424072265625, | |
| "learning_rate": 4.742871954380509e-05, | |
| "loss": 1.4921, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.6762199845081333, | |
| "eval_f1_macro": 0.36762215914350266, | |
| "eval_f1_micro": 0.6762199845081333, | |
| "eval_f1_weighted": 0.6381553142782734, | |
| "eval_loss": 1.0307424068450928, | |
| "eval_macro_fpr": 0.03508857639652692, | |
| "eval_macro_sensitivity": 0.4027183655220987, | |
| "eval_macro_specificity": 0.9746655126680946, | |
| "eval_precision": 0.6361951106730956, | |
| "eval_precision_macro": 0.3745780279088578, | |
| "eval_recall": 0.6762199845081333, | |
| "eval_recall_macro": 0.4027183655220987, | |
| "eval_runtime": 65.0146, | |
| "eval_samples_per_second": 19.857, | |
| "eval_steps_per_second": 2.492, | |
| "eval_weighted_fpr": 0.03306962025316456, | |
| "eval_weighted_sensitivity": 0.6762199845081333, | |
| "eval_weighted_specificity": 0.9437627055132857, | |
| "step": 643 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 9645, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 15, | |
| "save_steps": 500, | |
| "total_flos": 1352022394447872.0, | |
| "train_batch_size": 8, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |