albert-base-v2-wordnet_combined_one-fine-tuned
This model is a fine-tuned version of albert-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1222
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 |
|---|---|---|---|
| 0.249 | 1.0 | 7354 | 0.2601 |
| 0.1908 | 2.0 | 14708 | 0.1434 |
| 0.1485 | 3.0 | 22062 | 0.1222 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for Carick/albert-base-v2-wordnet_combined_one-fine-tuned
Base model
albert/albert-base-v2