### Description

The baseline NLI model is a fine-tuned version of *bert-base-uncased* 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

### Results on the validation set
```
MNLI: 90.07%
MNLI-mm: 90.08%
```

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- optimizer: "adamw_torch"
- lr_scheduler_type: linear
- num_epochs: 4

{"language": ["en"], "datasets": ["multi_nli"], "metrics": ["accuracy"], "pipeline_tag": "text-classification"}
transformers safetensors bert text-classification en dataset:multi_nli autotrain_compatible endpoints_compatible region:us