---
license: apache-2.0
base_model: studio-ousia/mluke-large-lite
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: out
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/rspeech3399/huggingface/runs/uv90lda8)
# out

This model is a fine-tuned version of [studio-ousia/mluke-large-lite](https://huggingface.co/studio-ousia/mluke-large-lite) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1615
- Accuracy: 0.9399
- Precision: 0.9346
- Recall: 0.9460
- F1: 0.9403

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4109        | 1.0   | 1479 | 0.2462          | 0.9003   | 0.8710    | 0.9399 | 0.9041 |
| 0.1579        | 2.0   | 2958 | 0.1573          | 0.9399   | 0.9495    | 0.9293 | 0.9393 |
| 0.114         | 3.0   | 4437 | 0.1615          | 0.9399   | 0.9346    | 0.9460 | 0.9403 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1