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---
base_model: roneneldan/TinyStories-33M
library_name: Distily
tags:
- generated_from_trainer
model-index:
- name: distily_bench_obj_cross
results: []
---
# distily_bench_obj_cross
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: 5102.7344
- eval_frwikippl: 36133.4453
- eval_zhwikippl: 51745.4414
- eval_tinystoriesppl: 1872.7611
- eval_loss: 17.3780
- eval_runtime: 33.2598
- eval_samples_per_second: 75.166
- eval_steps_per_second: 9.411
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
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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=10.0, loss_fn=raw_mse, layer_mapper=None, projector=None), attn_loss_component=LossComponent(label=attn, weight=10.0, loss_fn=raw_mse, layer_mapper=None, projector=None))
- train_embeddings: True
- learning_rate: 0.0004
- train_batch_size: 16
- 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: 16.2498 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 | 27673.0234 | 72839.8984 | 19.1728 | 33.1089 | 75.508 | 9.454 | 16450.7617 | 62570.5625 |
| 2000 | 0.1293 | 5104.3164 | 36174.1641 | 17.3784 | 33.2758 | 75.13 | 9.406 | 1874.0001 | 51745.4414 |
| 4000 | 0.2586 | 5104.3164 | 36214.9648 | 17.3776 | 33.0549 | 75.632 | 9.469 | 1873.0709 | 51773.0352 |
| 6000 | 0.3879 | 5104.3164 | 36133.4453 | 17.3784 | 33.0479 | 75.648 | 9.471 | 1874.3102 | 51717.8164 |
| 8000 | 0.5172 | 5102.7344 | 36133.4453 | 17.3780 | 33.2598 | 75.166 | 9.411 | 1872.7611 | 51745.4414 |
| 10000 | 0.6465 | 5105.8984 | 36133.4453 | 17.3784 | 33.2485 | 75.191 | 9.414 | 1875.8596 | 51745.4414 |
| 12000 | 0.7757 | 5105.8984 | 36133.4453 | 17.3780 | 33.0133 | 75.727 | 9.481 | 1874.9297 | 51717.8164 |
| 14000 | 0.9050 | 5104.3164 | 36214.9648 | 17.3776 | 33.2272 | 75.24 | 9.42 | 1872.7611 | 51745.4414 |
| 15469 | 1.0 | 5104.3164 | 36133.4453 | 17.3784 | 33.002 | 75.753 | 9.484 | 1874.3102 | 51745.4414 |
### Framework versions
- Distily 0.2.0
- Transformers 4.44.0
- Pytorch 2.3.0
- Datasets 2.21.0
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