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---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: Models-RoBERTa-1704501009.345538
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# 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