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---
base_model: gpt2
library_name: Distily
license: mit
tags:
- generated_from_trainer
model-index:
- name: distily_bench_obj_cross_v2.13_gpt2
results: []
---
# distily_bench_obj_cross_v2.13_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: 1376.0
- eval_frwikippl: 5824.0
- eval_zhwikippl: 101888.0
- eval_tinystoriesppl: 972.0
- eval_loss: 3.1064
- eval_runtime: 12.9246
- eval_samples_per_second: 46.423
- eval_steps_per_second: 11.606
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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## Model description
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## Intended uses & limitations
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## 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=1.0, loss_fn=cos, layer_mapper=uniform_cons, 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: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.5
- num_epochs: 1.0
### Resource Usage
Peak GPU Memory: 8.0905 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 | 1821066133504.0 | 158329674399744.0 | 20.2008 | 12.884 | 46.569 | 11.642 | 12079595520.0 | 98956046499840.0 |
| 750 | 0.1010 | 1376.0 | 5824.0 | 3.1064 | 12.9246 | 46.423 | 11.606 | 972.0 | 101888.0 |
| 1500 | 0.2020 | 584.0 | 3552.0 | 2.2186 | 12.958 | 46.304 | 11.576 | 438.0 | 1012.0 |
| 2250 | 0.3030 | 376.0 | 1888.0 | 1.9252 | 12.9544 | 46.316 | 11.579 | 312.0 | 366.0 |
| 3000 | 0.4040 | 266.0 | 1072.0 | 1.6667 | 13.0268 | 46.059 | 11.515 | 227.0 | 203.0 |
| 3750 | 0.5051 | 211.0 | 736.0 | 1.4766 | 12.9492 | 46.335 | 11.584 | 175.0 | 233.0 |
| 4500 | 0.6061 | 171.0 | 588.0 | 1.2986 | 13.0596 | 45.943 | 11.486 | 141.0 | 147.0 |
| 5250 | 0.7071 | 134.0 | 480.0 | 1.1348 | 12.9613 | 46.292 | 11.573 | 110.5 | 154.0 |
| 6000 | 0.8081 | 125.0 | 456.0 | 1.0662 | 12.9543 | 46.317 | 11.579 | 100.0 | 129.0 |
| 6750 | 0.9091 | 119.0 | 440.0 | 1.0325 | 12.9319 | 46.397 | 11.599 | 96.0 | 122.5 |
| 7425 | 1.0 | 118.0 | 436.0 | 1.0267 | 12.9764 | 46.238 | 11.559 | 94.5 | 122.0 |
### Framework versions
- Distily 0.2.0
- Transformers 4.44.0
- Pytorch 2.3.0
- Datasets 2.21.0
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