fine-tuned-albert-tweets
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: 0.1757
- Accuracy: 0.9305
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: 2e-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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3202 | 1.0 | 1000 | 0.2518 | 0.912 |
| 0.1537 | 2.0 | 2000 | 0.1757 | 0.9305 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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