metadata
base_model: gpt2
library_name: Distily
license: mit
tags:
- generated_from_trainer
model-index:
- name: distily_bench_obj_cross_v2.15_gpt2
results: []
distily_bench_obj_cross_v2.15_gpt2
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: 99.0
- eval_frwikippl: 408.0
- eval_zhwikippl: 149.0
- eval_tinystoriesppl: 74.5
- eval_loss: 0.7768
- eval_runtime: 16.7488
- eval_samples_per_second: 59.706
- eval_steps_per_second: 7.463
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- distillation_objective: DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl, layer_mapper=None, projector=None), hs_loss_component=LossComponent(label=hs, weight=0, loss_fn=None, layer_mapper=None, projector=None), attn_loss_component=LossComponent(label=attn, weight=0, loss_fn=None, layer_mapper=None, projector=None))
- train_embeddings: True
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 1.0
Resource Usage
Peak GPU Memory: 7.4226 GB
Eval-Phase Metrics
| step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | tinystoriesppl | zhwikippl |
|---|---|---|---|---|---|---|---|---|---|
| teacher eval | 43.75 | 61.75 | 11.8125 | 19.125 | |||||
| 0 | 0 | 10027008.0 | 5734400.0 | 11.3280 | 16.7303 | 59.772 | 7.471 | 5865472.0 | 3637248.0 |
| 1000 | 0.0404 | 382.0 | 2016.0 | 1.6270 | 16.7162 | 59.822 | 7.478 | 298.0 | 1200.0 |
| 2000 | 0.0808 | 270.0 | 988.0 | 1.4340 | 16.7294 | 59.775 | 7.472 | 227.0 | 390.0 |
| 3000 | 0.1212 | 218.0 | 736.0 | 1.2960 | 16.686 | 59.931 | 7.491 | 185.0 | 239.0 |
| 4000 | 0.1616 | 182.0 | 708.0 | 1.1629 | 16.7199 | 59.809 | 7.476 | 144.0 | 213.0 |
| 5000 | 0.2020 | 155.0 | 620.0 | 1.0601 | 16.7539 | 59.688 | 7.461 | 117.0 | 230.0 |
| 6000 | 0.2424 | 131.0 | 496.0 | 0.9643 | 16.7329 | 59.763 | 7.47 | 104.5 | 193.0 |
| 7000 | 0.2828 | 122.0 | 512.0 | 0.9001 | 16.7515 | 59.696 | 7.462 | 91.5 | 193.0 |
| 8000 | 0.3232 | 111.5 | 428.0 | 0.8336 | 16.677 | 59.963 | 7.495 | 82.5 | 161.0 |
| 9000 | 0.3636 | 99.0 | 408.0 | 0.7768 | 16.7488 | 59.706 | 7.463 | 74.5 | 149.0 |
| 10000 | 0.4040 | 89.5 | 386.0 | 0.7219 | 16.6219 | 60.162 | 7.52 | 71.5 | 140.0 |
| 11000 | 0.4444 | 82.5 | 332.0 | 0.6595 | 16.6753 | 59.969 | 7.496 | 67.0 | 148.0 |
| 12000 | 0.4848 | 78.0 | 300.0 | 0.6302 | 16.6631 | 60.013 | 7.502 | 60.75 | 131.0 |
| 13000 | 0.5253 | 73.5 | 292.0 | 0.6019 | 16.7166 | 59.821 | 7.478 | 59.5 | 117.0 |
| 14000 | 0.5657 | 75.0 | 284.0 | 0.5861 | 16.7002 | 59.88 | 7.485 | 59.5 | 137.0 |
| 15000 | 0.6061 | 71.5 | 252.0 | 0.5722 | 16.6732 | 59.976 | 7.497 | 55.25 | 130.0 |
| 16000 | 0.6465 | 70.0 | 250.0 | 0.5545 | 16.6934 | 59.904 | 7.488 | 57.75 | 104.5 |
| 17000 | 0.6869 | 70.0 | 272.0 | 0.5426 | 16.6888 | 59.92 | 7.49 | 55.5 | 130.0 |
| 18000 | 0.7273 | 70.0 | 248.0 | 0.5380 | 16.6762 | 59.966 | 7.496 | 53.75 | 124.0 |
| 19000 | 0.7677 | 68.5 | 227.0 | 0.5270 | 16.6682 | 59.994 | 7.499 | 53.5 | 96.5 |
| 20000 | 0.8081 | 65.5 | 219.0 | 0.5260 | 16.6778 | 59.96 | 7.495 | 52.0 | 129.0 |
| 21000 | 0.8485 | 68.0 | 228.0 | 0.5154 | 16.7388 | 59.741 | 7.468 | 52.0 | 140.0 |
| 22000 | 0.8889 | 68.5 | 246.0 | 0.5128 | 16.6637 | 60.011 | 7.501 | 51.75 | 216.0 |
| 23000 | 0.9293 | 64.5 | 245.0 | 0.5029 | 16.7201 | 59.808 | 7.476 | 52.5 | 146.0 |
| 24000 | 0.9697 | 66.5 | 230.0 | 0.5067 | 16.7059 | 59.859 | 7.482 | 51.25 | 168.0 |
| 24750 | 1.0 | 65.5 | 228.0 | 0.5042 | 16.685 | 59.934 | 7.492 | 51.25 | 100.5 |
Framework versions
- Distily 0.2.0
- Transformers 4.44.0
- Pytorch 2.3.0
- Datasets 2.21.0