istily_bench_gpt2_simple_objectives

distily_bench_gpt2_simple_objectives

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: 495.9718
• eval_frwikippl: 3345.0957
• eval_zhwikippl: 2696.0598
• eval_loss: 40.5622
• eval_runtime: 34.3051
• eval_samples_per_second: 58.3
• eval_steps_per_second: 7.288

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Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• distillation_objective: MultiObjective(logits_weight=1, logits_loss_fn=(fn:kl_divergence_loss()), activations_weight=0.2, activations_loss_fn=(fn:mse_loss()), attentions_weight=0, attentions_loss_fn=(fn:mse_loss()))
• train_embeddings: True
• learning_rate: 4e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• num_epochs: 1.0

Resource Usage

Peak GPU Memory: 8.0893 GB

Eval-Phase Metrics

Framework versions

• Distily 0.2.0
• Transformers 4.44.0
• Pytorch 2.3.0
• Datasets 2.20.0