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--- |
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base_model: roneneldan/TinyStories-33M |
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library_name: Distily |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: distily_bench_obj_cross_v2.2 |
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results: [] |
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--- |
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# distily_bench_obj_cross_v2.2 |
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This student model is distilled from the teacher model [roneneldan/TinyStories-33M](https://huggingface.co/roneneldan/TinyStories-33M) using the dataset (unspecified). |
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The [Distily](https://github.com/lapp0/distily) library was used for this distillation. |
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It achieves the following results on the evaluation set: |
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- eval_enwikippl: 28257.9004 |
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- eval_frwikippl: 63896.6680 |
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- eval_zhwikippl: 90059.6875 |
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- eval_tinystoriesppl: 18426.4922 |
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- eval_loss: 6.6740 |
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- eval_runtime: 13.137 |
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- eval_samples_per_second: 76.121 |
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- eval_steps_per_second: 9.515 |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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--> |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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)) |
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- train_embeddings: True |
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- learning_rate: 4e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- num_epochs: 1.0 |
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### Resource Usage |
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Peak GPU Memory: 8.0568 GB |
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### Eval-Phase Metrics |
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| step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | tinystoriesppl | zhwikippl | |
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| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | |
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| **teacher eval** | | 169.9865 | 47377.9414 | | | | | 3.9789 | 4998.1294 | |
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| 0 | 0 | 35507.3906 | 70936.2969 | 6.875 | 13.2774 | 75.316 | 9.414 | 24370.3125 | 92840.9844 | |
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| 500 | 0.0404 | 28284.1875 | 63896.6680 | 6.6737 | 13.1884 | 75.824 | 9.478 | 18447.8379 | 90059.6875 | |
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| 1000 | 0.0808 | 28284.1875 | 63896.6680 | 6.6740 | 13.221 | 75.637 | 9.455 | 18444.7754 | 90059.6875 | |
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| 1500 | 0.1212 | 28284.1875 | 63896.6680 | 6.6740 | 13.1643 | 75.963 | 9.495 | 18444.7754 | 90059.6875 | |
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| 2000 | 0.1616 | 28284.1875 | 63896.6680 | 6.6740 | 13.2331 | 75.568 | 9.446 | 18438.6914 | 90059.6875 | |
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| 2500 | 0.2020 | 28284.1875 | 63896.6680 | 6.6740 | 13.1865 | 75.835 | 9.479 | 18432.5898 | 90059.6875 | |
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| 3000 | 0.2424 | 28257.9004 | 63896.6680 | 6.6740 | 13.246 | 75.494 | 9.437 | 18426.4922 | 90059.6875 | |
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| 3500 | 0.2828 | 28257.9004 | 63896.6680 | 6.6740 | 13.1762 | 75.895 | 9.487 | 18426.4922 | 90059.6875 | |
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| 4000 | 0.3232 | 28257.9004 | 63896.6680 | 6.6740 | 13.3585 | 74.859 | 9.357 | 18426.4922 | 90059.6875 | |
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| 4500 | 0.3636 | 28257.9004 | 63896.6680 | 6.6740 | 13.1842 | 75.848 | 9.481 | 18426.4922 | 90059.6875 | |
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| 5000 | 0.4040 | 28257.9004 | 63896.6680 | 6.6740 | 13.2694 | 75.361 | 9.42 | 18426.4922 | 90059.6875 | |
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| 5500 | 0.4444 | 28257.9004 | 63896.6680 | 6.6740 | 13.2102 | 75.699 | 9.462 | 18426.4922 | 90059.6875 | |
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| 6000 | 0.4848 | 28257.9004 | 63896.6680 | 6.6740 | 13.3012 | 75.181 | 9.398 | 18426.4922 | 90059.6875 | |
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| 6500 | 0.5253 | 28257.9004 | 63896.6680 | 6.6740 | 13.1704 | 75.928 | 9.491 | 18426.4922 | 90059.6875 | |
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| 7000 | 0.5657 | 28257.9004 | 63896.6680 | 6.6740 | 13.2236 | 75.622 | 9.453 | 18426.4922 | 90059.6875 | |
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| 7500 | 0.6061 | 28257.9004 | 63896.6680 | 6.6740 | 13.2333 | 75.567 | 9.446 | 18426.4922 | 90059.6875 | |
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| 8000 | 0.6465 | 28257.9004 | 63896.6680 | 6.6740 | 13.1385 | 76.112 | 9.514 | 18426.4922 | 90059.6875 | |
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| 8500 | 0.6869 | 28257.9004 | 63896.6680 | 6.6740 | 13.2297 | 75.588 | 9.448 | 18426.4922 | 90059.6875 | |
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| 9000 | 0.7273 | 28257.9004 | 63896.6680 | 6.6740 | 13.1073 | 76.293 | 9.537 | 18426.4922 | 90059.6875 | |
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| 9500 | 0.7677 | 28257.9004 | 63896.6680 | 6.6740 | 13.137 | 76.121 | 9.515 | 18426.4922 | 90059.6875 | |
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| 10000 | 0.8081 | 28257.9004 | 63896.6680 | 6.6740 | 13.0862 | 76.417 | 9.552 | 18426.4922 | 90059.6875 | |
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| 10500 | 0.8485 | 28257.9004 | 63896.6680 | 6.6740 | 13.17 | 75.93 | 9.491 | 18426.4922 | 90059.6875 | |
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| 11000 | 0.8889 | 28257.9004 | 63896.6680 | 6.6740 | 13.211 | 75.694 | 9.462 | 18426.4922 | 90059.6875 | |
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| 11500 | 0.9293 | 28257.9004 | 63896.6680 | 6.6740 | 13.1171 | 76.237 | 9.53 | 18426.4922 | 90059.6875 | |
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| 12000 | 0.9697 | 28257.9004 | 63896.6680 | 6.6740 | 13.2484 | 75.481 | 9.435 | 18426.4922 | 90059.6875 | |
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| 12375 | 1.0 | 28257.9004 | 63896.6680 | 6.6740 | 13.2116 | 75.691 | 9.461 | 18426.4922 | 90059.6875 | |
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### Framework versions |
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- Distily 0.2.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.3.0 |
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- Datasets 2.20.0 |
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