Models-RoBERTa-1704501009.345538
This model is a fine-tuned version of 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
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