---
library_name: transformers
license: apache-2.0
base_model: studio-ousia/mluke-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 4be5da4a13273b95662f7a02b0747bee
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 4be5da4a13273b95662f7a02b0747bee

This model is a fine-tuned version of [studio-ousia/mluke-base](https://huggingface.co/studio-ousia/mluke-base) on the dair-ai/emotion [split] dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2213
- Data Size: 1.0
- Epoch Runtime: 48.6894
- Accuracy: 0.9304
- F1 Macro: 0.8766

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
| No log        | 0     | 0    | 1.8219          | 0         | 2.4193        | 0.0993   | 0.0601   |
| No log        | 1     | 500  | 1.5722          | 0.0078    | 3.1785        | 0.3589   | 0.1389   |
| No log        | 2     | 1000 | 1.5065          | 0.0156    | 4.0965        | 0.3503   | 0.0882   |
| No log        | 3     | 1500 | 1.5120          | 0.0312    | 5.9046        | 0.4612   | 0.1780   |
| No log        | 4     | 2000 | 1.1079          | 0.0625    | 7.0501        | 0.5842   | 0.2456   |
| 0.0678        | 5     | 2500 | 0.6385          | 0.125     | 9.8105        | 0.7828   | 0.6156   |
| 0.3896        | 6     | 3000 | 0.3752          | 0.25      | 15.5161       | 0.8695   | 0.8157   |
| 0.0379        | 7     | 3500 | 0.2447          | 0.5       | 26.9726       | 0.9138   | 0.8684   |
| 0.1801        | 8.0   | 4000 | 0.1651          | 1.0       | 49.3466       | 0.9289   | 0.8881   |
| 0.1285        | 9.0   | 4500 | 0.1754          | 1.0       | 49.2456       | 0.9254   | 0.8746   |
| 0.1204        | 10.0  | 5000 | 0.1674          | 1.0       | 48.8140       | 0.9340   | 0.8948   |
| 0.0959        | 11.0  | 5500 | 0.1805          | 1.0       | 46.6978       | 0.9259   | 0.8884   |
| 0.0903        | 12.0  | 6000 | 0.2213          | 1.0       | 48.6894       | 0.9304   | 0.8766   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1