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---
library_name: transformers
base_model: studio-ousia/luke-base-lite
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 1ccfffeacad1f0b9e6353344b490bd38
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. -->
# 1ccfffeacad1f0b9e6353344b490bd38
This model is a fine-tuned version of [studio-ousia/luke-base-lite](https://huggingface.co/studio-ousia/luke-base-lite) on the dair-ai/emotion [split] dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1864
- Data Size: 1.0
- Epoch Runtime: 45.3066
- Accuracy: 0.9279
- F1 Macro: 0.8799
## 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 | 1.8419 | 0 | 2.2204 | 0.0338 | 0.0128 |
| No log | 1 | 500 | 1.6823 | 0.0078 | 2.8052 | 0.2908 | 0.0751 |
| No log | 2 | 1000 | 1.5591 | 0.0156 | 3.1628 | 0.3488 | 0.0862 |
| No log | 3 | 1500 | 1.1409 | 0.0312 | 3.9978 | 0.5736 | 0.2364 |
| No log | 4 | 2000 | 0.7112 | 0.0625 | 5.6075 | 0.7601 | 0.6169 |
| 0.0506 | 5 | 2500 | 0.4577 | 0.125 | 8.4992 | 0.8387 | 0.7905 |
| 0.344 | 6 | 3000 | 0.2268 | 0.25 | 13.9797 | 0.9189 | 0.8742 |
| 0.0383 | 7 | 3500 | 0.2045 | 0.5 | 24.5039 | 0.9254 | 0.8853 |
| 0.1978 | 8.0 | 4000 | 0.1479 | 1.0 | 46.4312 | 0.9304 | 0.8919 |
| 0.1522 | 9.0 | 4500 | 0.1909 | 1.0 | 45.6419 | 0.9279 | 0.8888 |
| 0.1482 | 10.0 | 5000 | 0.2014 | 1.0 | 45.1532 | 0.9264 | 0.8917 |
| 0.1233 | 11.0 | 5500 | 0.1883 | 1.0 | 44.6967 | 0.9294 | 0.8932 |
| 0.1042 | 12.0 | 6000 | 0.1864 | 1.0 | 45.3066 | 0.9279 | 0.8799 |
### Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
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