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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: sileod/roberta-base-mnli
model-index:
- name: roberta2-base-mnli-negnli
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. -->
# roberta2-base-mnli-negnli
This model is a fine-tuned version of [sileod/roberta-base-mnli](https://huggingface.co/sileod/roberta-base-mnli) on the GLUE MNLI dataset and the [MNLI subset in NegNLI](https://github.com/mosharafhossain/negation-and-nli/tree/master/data/new_benchmarks/processed_for_run/MNLI).
It achieves the following results on the evaluation set:
- Loss: 0.8397
- Accuracy: 0.8400
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
### Training results
### Framework versions
- Transformers 4.21.0.dev0
- Pytorch 1.8.0
- Datasets 1.18.3
- Tokenizers 0.12.1
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