roberta-base-nsp-10000-1e-06-16
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2827
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-06
- train_batch_size: 64
- eval_batch_size: 1024
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 157 | 0.6924 |
0.6939 | 2.0 | 314 | 0.6904 |
0.6909 | 3.0 | 471 | 0.6734 |
0.6456 | 4.0 | 628 | 0.4767 |
0.6456 | 5.0 | 785 | 0.3638 |
0.4555 | 6.0 | 942 | 0.3189 |
0.3506 | 7.0 | 1099 | 0.3019 |
0.3029 | 8.0 | 1256 | 0.3013 |
0.2722 | 9.0 | 1413 | 0.3003 |
0.2722 | 10.0 | 1570 | 0.2986 |
0.2582 | 11.0 | 1727 | 0.2850 |
0.237 | 12.0 | 1884 | 0.2805 |
0.2182 | 13.0 | 2041 | 0.2884 |
0.2182 | 14.0 | 2198 | 0.2844 |
0.208 | 15.0 | 2355 | 0.2876 |
0.2026 | 16.0 | 2512 | 0.2927 |
0.1908 | 17.0 | 2669 | 0.2827 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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