lapp0/distily_bench_gpt2_linear_objectives
07
distilybenchgpt2_optim
This student model is distilled from the teacher model gpt2 using the dataset (unspecified).
The Distily library was used for this distillation.
It achieves the following results on the evaluation set:
- eval_enwikippl: 524.7870
- eval_frwikippl: 3705.5625
- eval_zhwikippl: 6035.2861
- eval_loss: 2370.7361
- eval_runtime: 21.6322
- evalsamplesper_second: 46.227
- evalstepsper_second: 11.557
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Model description
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Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- distillationobjective: LinearObjective(logitsweight=1, logitslossfn=<function kldivergenceloss at 0x7f57c4b07910>, activationsweight=10, activationslossfn=<function kldivergenceloss at 0x7f57c4b07910>, attentionsweight=0, attentionslossfn=<function mse_loss at 0x7f57c4b07880>)
- train_embeddings: True
- learning_rate: 4e-05
- trainbatchsize: 4
- evalbatchsize: 4
- seed: 42
- gradientaccumulationsteps: 4
- totaltrainbatch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lrschedulertype: constant
- num_epochs: 1.0
Resource Usage
Peak GPU Memory: 4.5067 GB
Eval-Phase Metrics
Framework versions
- Distily 0.2.0
- Transformers 4.44.0
- Pytorch 2.3.0
- Datasets 2.20.0
