---
base_model: roneneldan/TinyStories-33M
library_name: Distily
tags:
- generated_from_trainer
model-index:
- name: distily_bench_obj_cross_v2.2
  results: []
---

# distily_bench_obj_cross_v2.2

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: 28257.9004
- eval_frwikippl: 63896.6680
- eval_zhwikippl: 90059.6875
- eval_tinystoriesppl: 18426.4922
- eval_loss: 6.6740
- eval_runtime: 13.137
- eval_samples_per_second: 76.121
- eval_steps_per_second: 9.515

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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: 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: 8.0568 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 | 35507.3906 | 70936.2969 | 6.875 | 13.2774 | 75.316 | 9.414 | 24370.3125 | 92840.9844 |
| 500 | 0.0404 | 28284.1875 | 63896.6680 | 6.6737 | 13.1884 | 75.824 | 9.478 | 18447.8379 | 90059.6875 |
| 1000 | 0.0808 | 28284.1875 | 63896.6680 | 6.6740 | 13.221 | 75.637 | 9.455 | 18444.7754 | 90059.6875 |
| 1500 | 0.1212 | 28284.1875 | 63896.6680 | 6.6740 | 13.1643 | 75.963 | 9.495 | 18444.7754 | 90059.6875 |
| 2000 | 0.1616 | 28284.1875 | 63896.6680 | 6.6740 | 13.2331 | 75.568 | 9.446 | 18438.6914 | 90059.6875 |
| 2500 | 0.2020 | 28284.1875 | 63896.6680 | 6.6740 | 13.1865 | 75.835 | 9.479 | 18432.5898 | 90059.6875 |
| 3000 | 0.2424 | 28257.9004 | 63896.6680 | 6.6740 | 13.246 | 75.494 | 9.437 | 18426.4922 | 90059.6875 |
| 3500 | 0.2828 | 28257.9004 | 63896.6680 | 6.6740 | 13.1762 | 75.895 | 9.487 | 18426.4922 | 90059.6875 |
| 4000 | 0.3232 | 28257.9004 | 63896.6680 | 6.6740 | 13.3585 | 74.859 | 9.357 | 18426.4922 | 90059.6875 |
| 4500 | 0.3636 | 28257.9004 | 63896.6680 | 6.6740 | 13.1842 | 75.848 | 9.481 | 18426.4922 | 90059.6875 |
| 5000 | 0.4040 | 28257.9004 | 63896.6680 | 6.6740 | 13.2694 | 75.361 | 9.42 | 18426.4922 | 90059.6875 |
| 5500 | 0.4444 | 28257.9004 | 63896.6680 | 6.6740 | 13.2102 | 75.699 | 9.462 | 18426.4922 | 90059.6875 |
| 6000 | 0.4848 | 28257.9004 | 63896.6680 | 6.6740 | 13.3012 | 75.181 | 9.398 | 18426.4922 | 90059.6875 |
| 6500 | 0.5253 | 28257.9004 | 63896.6680 | 6.6740 | 13.1704 | 75.928 | 9.491 | 18426.4922 | 90059.6875 |
| 7000 | 0.5657 | 28257.9004 | 63896.6680 | 6.6740 | 13.2236 | 75.622 | 9.453 | 18426.4922 | 90059.6875 |
| 7500 | 0.6061 | 28257.9004 | 63896.6680 | 6.6740 | 13.2333 | 75.567 | 9.446 | 18426.4922 | 90059.6875 |
| 8000 | 0.6465 | 28257.9004 | 63896.6680 | 6.6740 | 13.1385 | 76.112 | 9.514 | 18426.4922 | 90059.6875 |
| 8500 | 0.6869 | 28257.9004 | 63896.6680 | 6.6740 | 13.2297 | 75.588 | 9.448 | 18426.4922 | 90059.6875 |
| 9000 | 0.7273 | 28257.9004 | 63896.6680 | 6.6740 | 13.1073 | 76.293 | 9.537 | 18426.4922 | 90059.6875 |
| 9500 | 0.7677 | 28257.9004 | 63896.6680 | 6.6740 | 13.137 | 76.121 | 9.515 | 18426.4922 | 90059.6875 |
| 10000 | 0.8081 | 28257.9004 | 63896.6680 | 6.6740 | 13.0862 | 76.417 | 9.552 | 18426.4922 | 90059.6875 |
| 10500 | 0.8485 | 28257.9004 | 63896.6680 | 6.6740 | 13.17 | 75.93 | 9.491 | 18426.4922 | 90059.6875 |
| 11000 | 0.8889 | 28257.9004 | 63896.6680 | 6.6740 | 13.211 | 75.694 | 9.462 | 18426.4922 | 90059.6875 |
| 11500 | 0.9293 | 28257.9004 | 63896.6680 | 6.6740 | 13.1171 | 76.237 | 9.53 | 18426.4922 | 90059.6875 |
| 12000 | 0.9697 | 28257.9004 | 63896.6680 | 6.6740 | 13.2484 | 75.481 | 9.435 | 18426.4922 | 90059.6875 |
| 12375 | 1.0 | 28257.9004 | 63896.6680 | 6.6740 | 13.2116 | 75.691 | 9.461 | 18426.4922 | 90059.6875 |

### Framework versions
- Distily 0.2.0
- Transformers 4.44.0
- Pytorch 2.3.0
- Datasets 2.20.0