alberti128b128l
This model is a fine-tuned version of linhd-postdata/alberti-bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8217
- Accuracy: 0.6824
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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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 |
|---|---|---|---|---|
| 1.0695 | 1.0 | 1407 | 0.9283 | 0.6367 |
| 0.8637 | 2.0 | 2814 | 0.8396 | 0.6715 |
| 0.7881 | 3.0 | 4221 | 0.8217 | 0.6824 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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