outputs
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0224
- Pearson: 0.8314
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: 8e-05
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Pearson |
---|---|---|---|---|
No log | 1.0 | 214 | 0.0256 | 0.7816 |
No log | 2.0 | 428 | 0.0251 | 0.8115 |
0.0355 | 3.0 | 642 | 0.0257 | 0.8186 |
0.0355 | 4.0 | 856 | 0.0220 | 0.8255 |
0.0133 | 5.0 | 1070 | 0.0226 | 0.8287 |
0.0133 | 6.0 | 1284 | 0.0220 | 0.8321 |
0.0133 | 7.0 | 1498 | 0.0224 | 0.8314 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1
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