Training in progress, step 61875

README.md

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+---
+base_model: gpt2
+library_name: Distily
+license: mit
+tags:
+- generated_from_trainer
+model-index:
+- name: distily_bench_gpt2_attn_part_2
+  results: []
+---
+
+# distily_bench_gpt2_attn_part_2
+
+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: 218.5393
+- eval_frwikippl: 1177.8887
+- eval_zhwikippl: 654.9657
+- eval_loss: 1.2101
+- eval_runtime: 84.5457
+- eval_samples_per_second: 59.14
+- eval_steps_per_second: 7.392
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+-->
+
+## 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: 7.9371 GB
+
+### Eval-Phase Metrics
+| step | epoch | enwikippl | frwikippl | loss | runtime | samples_per_second | steps_per_second | zhwikippl |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| **teacher eval** |  | 30.2086 | 57.2728 |  |  |  |  | 18.1784 |
+| 0 | 0 | 57642.0977 | 56387.75 | 5.8468 | 84.9344 | 58.869 | 7.359 | 54838.8008 |
+| 1000 | 0.0162 | 715.0994 | 4617.4824 | 1.8640 | 84.6424 | 59.072 | 7.384 | 16026.5967 |
+| 2000 | 0.0323 | 509.6366 | 2986.9795 | 1.6848 | 84.231 | 59.361 | 7.42 | 1765.5764 |
+| 3000 | 0.0485 | 427.6056 | 2689.4856 | 1.5835 | 84.4251 | 59.224 | 7.403 | 968.8549 |
+| 4000 | 0.0646 | 370.2697 | 2295.2737 | 1.4992 | 84.3656 | 59.266 | 7.408 | 1006.3041 |
+| 5000 | 0.0808 | 317.6974 | 1989.4651 | 1.4212 | 84.6665 | 59.055 | 7.382 | 1057.5557 |
+| 6000 | 0.0970 | 285.2802 | 1632.1284 | 1.3569 | 84.6806 | 59.045 | 7.381 | 874.1838 |
+| 7000 | 0.1131 | 256.3500 | 1458.8361 | 1.3018 | 84.4525 | 59.205 | 7.401 | 849.1024 |
+| 8000 | 0.1293 | 237.8977 | 1317.0640 | 1.2529 | 84.5727 | 59.121 | 7.39 | 639.9225 |
+| 9000 | 0.1455 | 218.5393 | 1177.8887 | 1.2101 | 84.5457 | 59.14 | 7.392 | 654.9657 |
+| 10000 | 0.1616 | 202.2269 | 1126.2368 | 1.1660 | 84.6055 | 59.098 | 7.387 | 699.7226 |
+| 11000 | 0.1778 | 184.4057 | 1090.2955 | 1.1237 | 84.6191 | 59.088 | 7.386 | 1601.5863 |
+| 12000 | 0.1939 | 170.1912 | 972.0627 | 1.0802 | 84.6016 | 59.101 | 7.388 | 663.8590 |
+| 13000 | 0.2101 | 160.8243 | 873.9529 | 1.0462 | 84.6676 | 59.054 | 7.382 | 817.5033 |
+| 14000 | 0.2263 | 153.4316 | 853.4323 | 1.0216 | 84.5669 | 59.125 | 7.391 | 789.6068 |
+| 15000 | 0.2424 | 144.5039 | 750.0720 | 0.9936 | 84.4757 | 59.189 | 7.399 | 497.9154 |
+| 16000 | 0.2586 | 139.1196 | 713.8004 | 0.9741 | 84.6689 | 59.054 | 7.382 | 499.2470 |
+| 17000 | 0.2747 | 136.0640 | 718.4965 | 0.9613 | 84.4587 | 59.201 | 7.4 | 691.9172 |
+| 18000 | 0.2909 | 132.3746 | 717.3322 | 0.9476 | 84.7695 | 58.983 | 7.373 | 511.1194 |
+| 19000 | 0.3071 | 131.7389 | 662.5851 | 0.9386 | 84.5077 | 59.166 | 7.396 | 483.8233 |
+| 20000 | 0.3232 | 128.0474 | 670.8112 | 0.9298 | 84.837 | 58.937 | 7.367 | 464.8238 |
+| 21000 | 0.3394 | 125.2350 | 678.9477 | 0.9209 | 84.6313 | 59.08 | 7.385 | 329.0456 |
+| 22000 | 0.3556 | 125.6929 | 674.8433 | 0.9162 | 84.9393 | 58.866 | 7.358 | 347.1923 |
+| 23000 | 0.3717 | 124.5367 | 630.1886 | 0.9094 | 85.9763 | 58.156 | 7.269 | 457.4956 |
+| 24000 | 0.3879 | 123.1902 | 665.5817 | 0.9071 | 85.0672 | 58.777 | 7.347 | 311.9309 |
+| 25000 | 0.4040 | 122.3417 | 641.2142 | 0.9017 | 85.0283 | 58.804 | 7.35 | 365.3137 |
+| 26000 | 0.4202 | 120.2694 | 624.0430 | 0.8953 | 85.056 | 58.785 | 7.348 | 319.8610 |
+| 27000 | 0.4364 | 120.1667 | 628.5027 | 0.8907 | 85.1161 | 58.743 | 7.343 | 319.6902 |
+| 28000 | 0.4525 | 118.2781 | 570.9954 | 0.8846 | 85.144 | 58.724 | 7.341 | 272.5736 |
+| 29000 | 0.4687 | 118.5724 | 595.4168 | 0.8842 | 85.137 | 58.729 | 7.341 | 268.9220 |
+| 30000 | 0.4848 | 119.3669 | 594.5359 | 0.8814 | 84.9629 | 58.849 | 7.356 | 331.3828 |
+| 31000 | 0.5010 | 117.9205 | 597.4355 | 0.8759 | 85.1582 | 58.714 | 7.339 | 352.8950 |
+| 32000 | 0.5172 | 119.1076 | 616.9991 | 0.8873 | 85.3053 | 58.613 | 7.327 | 333.6027 |
+| 33000 | 0.5333 | 117.0265 | 598.3629 | 0.8810 | 85.4345 | 58.524 | 7.316 | 329.0897 |
+| 34000 | 0.5495 | 116.5639 | 591.6924 | 0.8745 | 85.4331 | 58.525 | 7.316 | 284.6257 |
+| 35000 | 0.5657 | 116.2566 | 583.1194 | 0.8736 | 85.3062 | 58.612 | 7.327 | 312.5146 |
+| 36000 | 0.5818 | 114.5094 | 569.9497 | 0.8699 | 85.3486 | 58.583 | 7.323 | 316.7582 |
+| 37000 | 0.5980 | 115.3036 | 556.4886 | 0.8670 | 85.331 | 58.595 | 7.324 | 276.4224 |
+| 38000 | 0.6141 | 114.4916 | 616.9991 | 0.8652 | 85.326 | 58.599 | 7.325 | 257.0539 |
+| 39000 | 0.6303 | 113.8003 | 562.5639 | 0.8617 | 85.2521 | 58.65 | 7.331 | 249.4454 |
+| 40000 | 0.6465 | 113.2449 | 589.2362 | 0.8608 | 85.4264 | 58.53 | 7.316 | 303.6291 |
+| 41000 | 0.6626 | 113.5267 | 595.7949 | 0.8585 | 85.32 | 58.603 | 7.325 | 331.6926 |
+| 42000 | 0.6788 | 112.8149 | 594.4523 | 0.8579 | 84.9462 | 58.861 | 7.358 | 352.5180 |
+| 43000 | 0.6949 | 114.1189 | 599.4184 | 0.8609 | 84.9848 | 58.834 | 7.354 | 1005.4978 |
+| 44000 | 0.7111 | 113.6678 | 552.8904 | 0.8595 | 85.0096 | 58.817 | 7.352 | 1579.9192 |
+| 45000 | 0.7273 | 111.6644 | 655.0142 | 0.8554 | 85.0106 | 58.816 | 7.352 | 587.5825 |
+| 46000 | 0.7434 | 113.8180 | 577.0257 | 0.8590 | 85.0044 | 58.821 | 7.353 | 429.3204 |
+| 47000 | 0.7596 | 112.4737 | 534.5300 | 0.8557 | 84.9665 | 58.847 | 7.356 | 295.4299 |
+| 48000 | 0.7758 | 112.1945 | 534.9068 | 0.8529 | 85.0374 | 58.798 | 7.35 | 355.7813 |
+| 49000 | 0.7919 | 112.0117 | 588.8623 | 0.8545 | 85.2876 | 58.625 | 7.328 | 353.1778 |
+| 50000 | 0.8081 | 110.6717 | 554.0220 | 0.8475 | 84.9061 | 58.889 | 7.361 | 320.5880 |
+| 51000 | 0.8242 | 110.2171 | 533.4382 | 0.8444 | 84.9625 | 58.85 | 7.356 | 293.8561 |
+| 52000 | 0.8404 | 109.8668 | 550.0522 | 0.8477 | 84.9033 | 58.891 | 7.361 | 292.7595 |
+| 53000 | 0.8566 | 110.8953 | 522.9734 | 0.8430 | 84.9959 | 58.826 | 7.353 | 330.4548 |
+| 54000 | 0.8727 | 113.6325 | 566.0253 | 0.8537 | 85.3083 | 58.611 | 7.326 | 435.0919 |
+| 55000 | 0.8889 | 112.4562 | 600.7300 | 0.8536 | 85.3234 | 58.601 | 7.325 | 440.3524 |
+| 56000 | 0.9051 | 112.5611 | 593.0288 | 0.8587 | 85.3061 | 58.612 | 7.327 | 713.9750 |
+| 57000 | 0.9212 | 113.5531 | 569.5080 | 0.8588 | 85.2454 | 58.654 | 7.332 | 455.4841 |
+| 58000 | 0.9374 | 110.8006 | 523.5637 | 0.8485 | 85.2585 | 58.645 | 7.331 | 420.0204 |
+| 59000 | 0.9535 | 110.0631 | 563.5960 | 0.8472 | 85.1774 | 58.701 | 7.338 | 391.7394 |
+| 60000 | 0.9697 | 109.0000 | 534.9446 | 0.8436 | 85.2097 | 58.679 | 7.335 | 323.9015 |
+| 61000 | 0.9859 | 112.5698 | 560.3074 | 0.8420 | 85.18 | 58.699 | 7.337 | 256.8824 |
+| 61875 | 1.0 | 109.4750 | 562.8416 | 0.8412 | 85.1958 | 58.688 | 7.336 | 313.6015 |
+
+### Framework versions
+- Distily 0.2.0
+- Transformers 4.44.0
+- Pytorch 2.3.0
+- Datasets 2.20.0

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.44.0"
+}

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