---
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](https://huggingface.co./gpt2) using the dataset (unspecified).

The [Distily](https://github.com/lapp0/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

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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:
- 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