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fine-tuning
This model is a fine-tuned version of roberta-large-mnli on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2517
- Mse: 0.2704
- Mae: 0.5037
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: 8
- eval_batch_size: 8
- 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 | Mse | Mae |
|---|---|---|---|---|---|
| No log | 0.24 | 100 | 0.2547 | 0.2725 | 0.5037 |
| No log | 0.48 | 200 | 0.2680 | 0.2769 | 0.5043 |
| No log | 0.72 | 300 | 0.2720 | 0.2780 | 0.5044 |
| No log | 0.95 | 400 | 0.2735 | 0.2784 | 0.5044 |
| 0.2943 | 1.19 | 500 | 0.2513 | 0.2652 | 0.5032 |
| 0.2943 | 1.43 | 600 | 0.2565 | 0.2731 | 0.5040 |
| 0.2943 | 1.67 | 700 | 0.2633 | 0.2755 | 0.5042 |
| 0.2943 | 1.91 | 800 | 0.2534 | 0.2640 | 0.5030 |
| 0.2943 | 2.15 | 900 | 0.2503 | 0.2691 | 0.5036 |
| 0.2675 | 2.39 | 1000 | 0.2511 | 0.2654 | 0.5032 |
| 0.2675 | 2.63 | 1100 | 0.2563 | 0.2730 | 0.5040 |
| 0.2675 | 2.86 | 1200 | 0.2528 | 0.2712 | 0.5038 |
| 0.2675 | 3.1 | 1300 | 0.2534 | 0.2640 | 0.5030 |
| 0.2675 | 3.34 | 1400 | 0.2520 | 0.2707 | 0.5037 |
| 0.2636 | 3.58 | 1500 | 0.2503 | 0.2690 | 0.5036 |
| 0.2636 | 3.82 | 1600 | 0.2517 | 0.2704 | 0.5037 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
