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library_name: transformers
license: apache-2.0
base_model: albert/albert-xxlarge-v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 27afceb9392c23d1674a5a2901ca7d34
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. -->
# 27afceb9392c23d1674a5a2901ca7d34
This model is a fine-tuned version of [albert/albert-xxlarge-v2](https://huggingface.co/albert/albert-xxlarge-v2) on the dair-ai/emotion [split] dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3531
- Data Size: 1.0
- Epoch Runtime: 41.1003
- Accuracy: 0.9088
- F1 Macro: 0.8659
## 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 | 2.2406 | 0 | 1.9154 | 0.0938 | 0.0641 |
| No log | 1 | 500 | 1.7164 | 0.0078 | 2.2981 | 0.2359 | 0.1245 |
| No log | 2 | 1000 | 1.7238 | 0.0156 | 2.6170 | 0.2747 | 0.1135 |
| No log | 3 | 1500 | 1.5864 | 0.0312 | 3.4158 | 0.3508 | 0.0944 |
| No log | 4 | 2000 | 1.5906 | 0.0625 | 4.7034 | 0.3054 | 0.1008 |
| 0.0883 | 5 | 2500 | 1.4474 | 0.125 | 7.0518 | 0.5050 | 0.2052 |
| 1.3713 | 6 | 3000 | 1.3480 | 0.25 | 12.0165 | 0.5469 | 0.2198 |
| 0.1954 | 7 | 3500 | 1.0987 | 0.5 | 21.9685 | 0.6144 | 0.2500 |
| 0.4637 | 8.0 | 4000 | 0.4034 | 1.0 | 41.8969 | 0.8831 | 0.7363 |
| 0.4674 | 9.0 | 4500 | 0.4547 | 1.0 | 41.4539 | 0.8866 | 0.7876 |
| 0.3519 | 10.0 | 5000 | 0.3257 | 1.0 | 41.3873 | 0.9057 | 0.8543 |
| 0.2821 | 11.0 | 5500 | 0.2998 | 1.0 | 41.3973 | 0.9113 | 0.8625 |
| 0.2597 | 12.0 | 6000 | 0.2644 | 1.0 | 41.4418 | 0.9148 | 0.8722 |
| 0.2649 | 13.0 | 6500 | 0.3314 | 1.0 | 41.2494 | 0.9158 | 0.8698 |
| 0.255 | 14.0 | 7000 | 0.2704 | 1.0 | 41.4583 | 0.9113 | 0.8641 |
| 0.1864 | 15.0 | 7500 | 0.3561 | 1.0 | 41.3138 | 0.9178 | 0.8721 |
| 0.2955 | 16.0 | 8000 | 0.3531 | 1.0 | 41.1003 | 0.9088 | 0.8659 |
### Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
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