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text_analyzer_albert-base-v3
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: 0.6595
- Accuracy: 0.9663
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: 0.1
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 15.7367 | 1.0 | 1303 | 15.8615 | 0.9663 |
| 4.8046 | 2.0 | 2606 | 3.7423 | 0.9663 |
| 6.7443 | 3.0 | 3909 | 0.8369 | 0.9663 |
| 2.3222 | 4.0 | 5212 | 0.6595 | 0.9663 |
Framework versions
- Transformers 4.29.1
- Pytorch 1.13.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
