fresh-2-layer-piqa10000-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: 12.9939
- Accuracy: 0.5101
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 | 0.32 | 100 | 19.1271 | 0.2879 |
No log | 0.64 | 200 | 13.9385 | 0.3687 |
No log | 0.96 | 300 | 13.3742 | 0.4040 |
No log | 1.28 | 400 | 13.6512 | 0.4293 |
2.752 | 1.6 | 500 | 13.0455 | 0.3838 |
2.752 | 1.92 | 600 | 15.1798 | 0.4293 |
2.752 | 2.24 | 700 | 13.8055 | 0.4545 |
2.752 | 2.56 | 800 | 13.9917 | 0.4394 |
2.752 | 2.88 | 900 | 13.5923 | 0.4899 |
0.9799 | 3.19 | 1000 | 13.3283 | 0.4545 |
0.9799 | 3.51 | 1100 | 12.5037 | 0.4798 |
0.9799 | 3.83 | 1200 | 13.9429 | 0.4545 |
0.9799 | 4.15 | 1300 | 12.9939 | 0.5101 |
0.9799 | 4.47 | 1400 | 13.7332 | 0.4899 |
0.5295 | 4.79 | 1500 | 13.9869 | 0.4596 |
0.5295 | 5.11 | 1600 | 12.5349 | 0.4747 |
0.5295 | 5.43 | 1700 | 12.5107 | 0.5 |
0.5295 | 5.75 | 1800 | 13.0188 | 0.5 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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