---
base_model: roneneldan/TinyStories-33M
library_name: Distily
tags:
- generated_from_trainer
model-index:
- name: distily_bench_obj_cross_v2.10
  results: []
---

# distily_bench_obj_cross_v2.10

This student model is distilled from the teacher model [roneneldan/TinyStories-33M](https://huggingface.co/roneneldan/TinyStories-33M) 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: 4839.0244
- eval_frwikippl: 39016.5469
- eval_zhwikippl: 56057.3555
- eval_tinystoriesppl: 1738.1987
- eval_loss: 4.8480
- eval_runtime: 13.0187
- eval_samples_per_second: 76.813
- eval_steps_per_second: 9.602

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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: 1e-06
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Resource Usage
Peak GPU Memory: 6.6048 GB

### Eval-Phase Metrics
| step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | tinystoriesppl | zhwikippl |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| **teacher eval** |  | 169.9865 | 47377.9414 |  |  |  |  | 3.9789 | 4998.1294 |
| 0 | 0 | 23326.0117 | 54995.6562 | 6.1135 | 13.0206 | 76.802 | 9.6 | 17003.8281 | 65438.9492 |
| 5000 | 0.0505 | 4839.0244 | 39016.5469 | 4.8478 | 13.0137 | 76.842 | 9.605 | 1738.1987 | 56102.2266 |
| 10000 | 0.1010 | 4839.0244 | 39016.5469 | 4.8480 | 12.9688 | 77.108 | 9.639 | 1738.1987 | 56087.25 |
| 15000 | 0.1515 | 4839.0244 | 39016.5469 | 4.8488 | 12.9532 | 77.201 | 9.65 | 1739.0610 | 56102.2266 |
| 20000 | 0.2020 | 4839.0244 | 39016.5469 | 4.8488 | 13.014 | 76.84 | 9.605 | 1738.4856 | 56072.2734 |
| 25000 | 0.2525 | 4839.0244 | 39016.5469 | 4.8485 | 13.0041 | 76.899 | 9.612 | 1738.1987 | 56057.3555 |
| 30000 | 0.3030 | 4839.0244 | 39016.5469 | 4.8488 | 12.9823 | 77.028 | 9.629 | 1738.4856 | 56057.3555 |
| 35000 | 0.3535 | 4839.0244 | 39016.5469 | 4.8485 | 13.037 | 76.705 | 9.588 | 1739.0610 | 56072.2734 |
| 40000 | 0.4040 | 4839.0244 | 39016.5469 | 4.8482 | 12.9918 | 76.972 | 9.621 | 1738.1987 | 56057.3555 |
| 45000 | 0.4545 | 4839.0244 | 38994.5625 | 4.8485 | 12.9951 | 76.952 | 9.619 | 1738.7732 | 56057.3555 |
| 50000 | 0.5051 | 4839.0244 | 39016.5469 | 4.8482 | 12.9731 | 77.083 | 9.635 | 1739.3488 | 56072.2734 |
| 55000 | 0.5556 | 4839.0244 | 39016.5469 | 4.8478 | 12.9694 | 77.105 | 9.638 | 1738.4856 | 56057.3555 |
| 60000 | 0.6061 | 4839.0244 | 39016.5469 | 4.8488 | 13.0353 | 76.715 | 9.589 | 1738.7732 | 56057.3555 |
| 65000 | 0.6566 | 4839.0244 | 39016.5469 | 4.8478 | 13.0087 | 76.872 | 9.609 | 1738.1987 | 56057.3555 |
| 70000 | 0.7071 | 4839.0244 | 39016.5469 | 4.8485 | 13.033 | 76.728 | 9.591 | 1738.1987 | 56057.3555 |
| 75000 | 0.7576 | 4839.0244 | 39016.5469 | 4.8480 | 13.0328 | 76.729 | 9.591 | 1738.4856 | 56057.3555 |
| 80000 | 0.8081 | 4839.0244 | 39016.5469 | 4.8482 | 12.9884 | 76.992 | 9.624 | 1737.9111 | 56057.3555 |
| 85000 | 0.8586 | 4839.0244 | 39016.5469 | 4.8485 | 13.0047 | 76.895 | 9.612 | 1738.1987 | 56087.25 |
| 90000 | 0.9091 | 4839.0244 | 39016.5469 | 4.8478 | 13.0255 | 76.772 | 9.597 | 1738.1987 | 56057.3555 |
| 95000 | 0.9596 | 4839.0244 | 39016.5469 | 4.8482 | 13.0007 | 76.919 | 9.615 | 1738.1987 | 56057.3555 |
| 99000 | 1.0 | 4839.0244 | 39016.5469 | 4.8480 | 13.0187 | 76.813 | 9.602 | 1738.1987 | 56057.3555 |

### Framework versions
- Distily 0.2.0
- Transformers 4.44.0
- Pytorch 2.3.0
- Datasets 2.21.0