--- license: mit base_model: roberta-base tags: - generated_from_trainer model-index: - name: Models-RoBERTa-1704501009.345538 results: [] --- # Models-RoBERTa-1704501009.345538 This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an MNLI dataset. It achieves the following results on the evaluation set (1000 instances of MNLI validation matched): - eval_loss: 0.2357 - eval_accuracy: 0.92 - eval_runtime: 7.4465 - eval_samples_per_second: 134.292 - eval_steps_per_second: 4.297 - epoch: 1.03 - step: 12597 ## Model description The baseline NLI model is a fine-tuned version of *roberta-base* for Text Classifacation on the MNLI dataset , with entailments as label 0 and all others (neutral or contradiction) as label 1. Two classes: * entailment: 0 * non-entailment: 1 ## Intended uses & limitations More information needed ## Training and evaluation data Model's performance on the validation sets: ``` MNLI: 92.07% MNLI-mm: 92.09% ``` ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.0