---
license: mit
language:
  - ja
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
- bert
datasets:
- MoritzLaurer/multilingual-NLI-26lang-2mil7
- shunk031/JGLUE
metrics:
- accuracy
- f1
model-index:
- name: mDeBERTa-v3-base-finetuned-nli-jnli
  results: []
pipeline_tag: zero-shot-classification
widget:
  - text: 明日の予定を教えて
---

<!-- 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. -->

# mDeBERTa-v3-base-finetuned-nli-jnli

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7739
- Accuracy: 0.6808
- F1: 0.6742

## 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: 3e-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
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.753         | 0.53  | 5000  | 0.8758          | 0.6105   | 0.6192 |
| 0.5947        | 1.07  | 10000 | 0.6619          | 0.7054   | 0.7035 |
| 0.5791        | 1.6   | 15000 | 0.7739          | 0.6808   | 0.6742 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3