Emotion_Albert
This model is a fine-tuned version of albert-base-v2 on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1537
- Accuracy: 0.9295
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 0.3094 | 1.0 | 1000 | 0.2669 | 0.9145 |
| 0.1776 | 2.0 | 2000 | 0.2013 | 0.928 |
| 0.1129 | 3.0 | 3000 | 0.1541 | 0.936 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for elyadenysova/Emotion_Albert
Base model
albert/albert-base-v2