fresh-2-layer-swag50000-distill-of-fresh-2-layer-gpqa_EVAL_gpqa
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 11.8130
- Accuracy: 0.5404
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 321
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 0.06 | 100 | 14.8090 | 0.2525 |
No log | 0.13 | 200 | 21.7092 | 0.3636 |
No log | 0.19 | 300 | 18.5664 | 0.3586 |
No log | 0.26 | 400 | 17.2545 | 0.4091 |
2.298 | 0.32 | 500 | 14.6083 | 0.4646 |
2.298 | 0.38 | 600 | 16.9225 | 0.4697 |
2.298 | 0.45 | 700 | 14.4167 | 0.4747 |
2.298 | 0.51 | 800 | 14.2497 | 0.4949 |
2.298 | 0.58 | 900 | 12.1858 | 0.5202 |
0.6557 | 0.64 | 1000 | 12.1346 | 0.5101 |
0.6557 | 0.7 | 1100 | 12.0078 | 0.5101 |
0.6557 | 0.77 | 1200 | 11.9163 | 0.5354 |
0.6557 | 0.83 | 1300 | 13.2215 | 0.4899 |
0.6557 | 0.9 | 1400 | 11.8032 | 0.5051 |
0.4142 | 0.96 | 1500 | 11.8130 | 0.5404 |
0.4142 | 1.02 | 1600 | 11.6673 | 0.5253 |
0.4142 | 1.09 | 1700 | 11.6830 | 0.4798 |
0.4142 | 1.15 | 1800 | 11.5380 | 0.4949 |
0.4142 | 1.22 | 1900 | 12.0938 | 0.5101 |
0.2783 | 1.28 | 2000 | 11.6623 | 0.5202 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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