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lapp0/distily_experiments_loss_kl
distily_experiments_loss_kl is a machine learning model from lapp0. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for distily. The card lists the license as apache-2.0.
This student model is distilled from the teacher model Qwen/Qwen2-0.5B-Instruct using the dataset (unspecified).
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From the Hugging Face model README
This student model is distilled from the teacher model Qwen/Qwen2-0.5B-Instruct using the dataset (unspecified).
The Distily library was used for this distillation.
It achieves the following results on the evaluation set:
The following hyperparameters were used during training:
Peak GPU Memory: 18.5713 GB
| step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | zhwikippl |
|---|---|---|---|---|---|---|---|---|
| teacher eval | 13.0697 | 11.6518 | 21.6262 | |||||
| 0 | 0 | 182369.3906 | 181455.125 | 780.3353 | 91.2363 | 10.961 | 2.74 | 180761.6719 |
| 500 | 0.0808 | 86362.2812 | 101159.6328 | 54.5867 | 91.4066 | 10.94 | 2.735 | 232064.5 |
| 1000 | 0.1616 | 69487.6797 | 86111.1172 | 53.6604 | 91.4579 | 10.934 | 2.733 | 345169.5312 |
| 1500 | 0.2424 | 82681.5703 | 89315.8984 | 35.7168 | 91.5034 | 10.929 | 2.732 | 445378.8125 |
| 2000 | 0.3232 | 57160.3164 | 68079.1016 | 35.2824 | 91.7023 | 10.905 | 2.726 | 518689.375 |
| 2500 | 0.4040 | 51816.1094 | 64056.9492 | 35.1557 | 91.637 | 10.913 | 2.728 | 541196.6875 |
| 3000 | 0.4848 | 48757.2461 | 61247.7969 | 34.9901 | 91.7102 | 10.904 | 2.726 | 490950.375 |
| 3500 | 0.5657 | 46986.8359 | 60241.9648 | 34.8887 | 91.7509 | 10.899 | 2.725 | 494001.2812 |
| 4000 | 0.6465 | 45312.1992 | 58663.0117 | 34.8189 | 91.5035 | 10.929 | 2.732 | 481694.25 |
| 4500 | 0.7273 | 44666.1914 | 58929.5781 | 34.8044 | 91.6675 | 10.909 | 2.727 | 422349.9062 |
| 5000 | 0.8081 | 44634.5938 | 59004.7656 | 34.6895 | 91.5871 | 10.919 | 2.73 | 366104.7188 |
| 5500 | 0.8889 | 43732.4805 | 57270.8125 | 34.6591 | 91.6394 | 10.912 | 2.728 | 369470.4688 |
| 6000 | 0.9697 | 43799.5938 | 57096.7930 | 34.6125 | 91.6634 | 10.909 | 2.727 | 372021.5 |
| 6187 | 0.9999 | 44644.5977 | 57738.3242 | 34.5918 | 91.6837 | 10.907 | 2.727 | 350857.0312 |