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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: 148.8680
- eval_frwikippl: 21987.7637
- eval_zhwikippl: 181662.0469
- eval_tinystoriesppl: 12.2941
- eval_loss: 25.4402
- eval_runtime: 66.3462
- eval_samples_per_second: 75.362
- eval_steps_per_second: 9.42
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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=10.0, loss_fn=kl, layer_mapper=None, projector=None), attn_loss_component=LossComponent(label=attn, weight=10.0, loss_fn=mse, layer_mapper=None, projector=None))
- train_embeddings: True
- learning_rate: 0.004
- 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: 8.2666 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 | 8167.3613 | 48488.5742 | 38.4688 | 65.8686 | 75.909 | 9.489 | 3345.3254 | 73944.1484 |
| 3000 | 0.0485 | 145.5666 | 22094.8828 | 25.4406 | 65.8501 | 75.93 | 9.491 | 11.9420 | 179685.7344 |
| 6000 | 0.0970 | 146.8635 | 22376.7676 | 25.4394 | 66.4135 | 75.286 | 9.411 | 11.9667 | 183024.1719 |
| 9000 | 0.1455 | 148.8680 | 21987.7637 | 25.4402 | 66.3462 | 75.362 | 9.42 | 12.2941 | 181662.0469 |
| 12000 | 0.1939 | 151.0636 | 22504.7676 | 25.4400 | 66.2246 | 75.501 | 9.438 | 12.5052 | 181759.0938 |
| 15000 | 0.2424 | 146.5339 | 22604.8535 | 25.4392 | 66.1192 | 75.621 | 9.453 | 11.8540 | 189888.4375 |
| 18000 | 0.2909 | 147.3192 | 22481.0215 | 25.4400 | 66.2457 | 75.477 | 9.435 | 12.0058 | 183905.2969 |
| 21000 | 0.3394 | 150.9525 | 22555.5625 | 25.4390 | 66.2661 | 75.453 | 9.432 | 12.4310 | 188575.7344 |
| 24000 | 0.3879 | 149.8920 | 22155.6523 | 25.4404 | 66.2363 | 75.487 | 9.436 | 12.4593 | 177493.9531 |
| 27000 | 0.4364 | 147.1653 | 22531.7402 | 25.4398 | 66.3823 | 75.321 | 9.415 | 11.9514 | 183905.2969 |
| 30000 | 0.4848 | 150.4855 | 22580.9805 | 25.4400 | 66.2281 | 75.497 | 9.437 | 12.4172 | 183513.1875 |
| 33000 | 0.5333 | 145.7359 | 22307.5195 | 25.4400 | 66.4448 | 75.25 | 9.406 | 11.9159 | 180165.8438 |
| 36000 | 0.5818 | 148.7297 | 22495.2617 | 25.4396 | 66.2715 | 75.447 | 9.431 | 12.1426 | 186574.0156 |
| 39000 | 0.6303 | 147.5820 | 22807.9492 | 25.4406 | 66.6342 | 75.037 | 9.38 | 11.9944 | 187372.1406 |
| 42000 | 0.6788 | 150.2292 | 22193.125 | 25.4402 | 66.5873 | 75.089 | 9.386 | 12.5202 | 182050.1875 |
| 45000 | 0.7273 | 146.7725 | 22207.2051 | 25.4400 | 66.1476 | 75.589 | 9.449 | 11.9890 | 181468.2812 |
| 48000 | 0.7758 | 146.3014 | 22194.6914 | 25.4398 | 66.4166 | 75.282 | 9.41 | 11.9746 | 177588.7812 |
| 51000 | 0.8242 | 148.6375 | 22533.3301 | 25.4402 | 66.2612 | 75.459 | 9.432 | 12.1471 | 186275.5156 |
| 54000 | 0.8727 | 147.6220 | 22394.1035 | 25.4404 | 66.4085 | 75.292 | 9.411 | 12.1140 | 185581.1406 |
| 57000 | 0.9212 | 148.8161 | 22679.8047 | 25.4400 | 66.3328 | 75.377 | 9.422 | 12.1230 | 187872.7812 |
| 60000 | 0.9697 | 146.8180 | 22345.2695 | 25.4392 | 66.5261 | 75.158 | 9.395 | 12.0317 | 181371.5625 |
| 61875 | 1.0 | 149.0526 | 22099.5410 | 25.4400 | 66.498 | 75.19 | 9.399 | 12.3048 | 181371.5625 |
### Framework versions
- Distily 0.2.0
- Transformers 4.44.0
- Pytorch 2.3.0
- Datasets 2.20.0
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