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lapp0/distily_experiments_loss_reverse_kl
distily_experiments_loss_reverse_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: 19.8832 GB
| step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | zhwikippl |
|---|---|---|---|---|---|---|---|---|
| teacher eval | 13.0697 | 11.6518 | 21.6262 | |||||
| 0 | 0 | 180187.8438 | 182062.6875 | 131.8108 | 90.6539 | 11.031 | 2.758 | 181762.375 |
| 500 | 0.0808 | 14699.2041 | 52797.9922 | 6.0418 | 90.8884 | 11.003 | 2.751 | 371252.0312 |
| 1000 | 0.1616 | 8812.4561 | 47709.9297 | 4.9882 | 90.8533 | 11.007 | 2.752 | 384212.3438 |
| 1500 | 0.2424 | 7321.3081 | 44922.375 | 4.6195 | 90.7179 | 11.023 | 2.756 | 400192.5625 |
| 2000 | 0.3232 | 6277.4165 | 42254.6719 | 4.2012 | 90.8257 | 11.01 | 2.753 | 423631.0938 |
| 2500 | 0.4040 | 5452.0264 | 39927.7812 | 3.9955 | 90.7803 | 11.016 | 2.754 | 445022.5938 |
| 3000 | 0.4848 | 4708.5049 | 37660.8359 | 3.7784 | 90.8232 | 11.01 | 2.753 | 447453.4375 |
| 3500 | 0.5657 | 4329.6147 | 35350.4805 | 3.6816 | 90.8654 | 11.005 | 2.751 | 455292.8125 |
| 4000 | 0.6465 | 3840.0864 | 33493.6836 | 3.5800 | 90.7858 | 11.015 | 2.754 | 446474.3125 |
| 4500 | 0.7273 | 3495.4482 | 31764.3340 | 3.4447 | 90.8083 | 11.012 | 2.753 | 447611.3438 |
| 5000 | 0.8081 | 3245.5376 | 30812.8379 | 3.3323 | 90.7976 | 11.014 | 2.753 | 448982.8438 |
| 5500 | 0.8889 | 3057.9595 | 29516.0742 | 3.2926 | 90.7385 | 11.021 | 2.755 | 459842.8125 |
| 6000 | 0.9697 | 2831.3643 | 28517.0625 | 3.1956 | 90.7677 | 11.017 | 2.754 | 441979.4375 |
| 6187 | 0.9999 | 2760.3779 | 28158.2578 | 3.1654 | 90.8509 | 11.007 | 2.752 | 441247.4688 |