---
base_model: huggingface/distilbert-base-uncased-finetuned-mnli
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-mnli-finetuned-voxi-mnli
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-uncased-finetuned-mnli-finetuned-voxi-mnli

This model is a fine-tuned version of [huggingface/distilbert-base-uncased-finetuned-mnli](https://huggingface.co/huggingface/distilbert-base-uncased-finetuned-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7457
- Accuracy: 0.8367

## 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: 5e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.0