output_mlm
This model is a fine-tuned version of roberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2024
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5832 | 0.19 | 15000 | 1.4992 |
| 1.5325 | 0.39 | 30000 | 1.4653 |
| 1.4979 | 0.58 | 45000 | 1.4359 |
| 1.4715 | 0.77 | 60000 | 1.4039 |
| 1.4448 | 0.97 | 75000 | 1.3877 |
| 1.4191 | 1.16 | 90000 | 1.3603 |
| 1.3988 | 1.35 | 105000 | 1.3425 |
| 1.3699 | 1.54 | 120000 | 1.3230 |
| 1.3493 | 1.74 | 135000 | 1.3012 |
| 1.3201 | 1.93 | 150000 | 1.2773 |
| 1.2993 | 2.12 | 165000 | 1.2617 |
| 1.2745 | 2.32 | 180000 | 1.2490 |
| 1.2614 | 2.51 | 195000 | 1.2283 |
| 1.2424 | 2.7 | 210000 | 1.2152 |
| 1.2296 | 2.9 | 225000 | 1.2052 |
Framework versions
- Transformers 4.11.2
- Pytorch 1.9.0
- Datasets 1.12.1
- Tokenizers 0.10.3
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