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distilr2-lr2e05-wd0.08-bs32
This model is a fine-tuned version of distilroberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2807
- Rmse: 0.5298
- Mse: 0.2807
- Mae: 0.4198
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: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Rmse | Mse | Mae |
---|---|---|---|---|---|---|
0.277 | 1.0 | 623 | 0.2730 | 0.5225 | 0.2730 | 0.4164 |
0.2731 | 2.0 | 1246 | 0.2732 | 0.5227 | 0.2732 | 0.4151 |
0.271 | 3.0 | 1869 | 0.2802 | 0.5293 | 0.2802 | 0.4319 |
0.2681 | 4.0 | 2492 | 0.2748 | 0.5242 | 0.2748 | 0.4012 |
0.2648 | 5.0 | 3115 | 0.2798 | 0.5290 | 0.2798 | 0.4250 |
0.2608 | 6.0 | 3738 | 0.2807 | 0.5298 | 0.2807 | 0.4198 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 2.4.0
- Tokenizers 0.12.1