End of training

README.md

@@ -16,14 +16,14 @@ This student model is distilled from the teacher model [gpt2](https://huggingfac
 The [Distily](https://github.com/lapp0/distily) library was used for this distillation.
 
 It achieves the following results on the evaluation set:
-- eval_enwikippl: 5056.0
-- eval_frwikippl: 3696.0
-- eval_zhwikippl: 29312.0
-- eval_tinystoriesppl: 4672.0
-- eval_loss: 1.3042
-- eval_runtime: 16.773
-- eval_samples_per_second: 59.62
-- eval_steps_per_second: 7.452
+- eval_enwikippl: 560.0
+- eval_frwikippl: 644.0
+- eval_zhwikippl: 488.0
+- eval_tinystoriesppl: 284.0
+- eval_loss: 0.6086
+- eval_runtime: 16.7587
+- eval_samples_per_second: 59.67
+- eval_steps_per_second: 7.459
 
 <!-- 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.
@@ -48,8 +48,8 @@ More information needed
 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: 0.0004
-- train_batch_size: 8
+- learning_rate: 0.0001
+- train_batch_size: 4
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
@@ -58,26 +58,38 @@ The following hyperparameters were used during training:
 - num_epochs: 1.0
 
 ### Resource Usage
-Peak GPU Memory: 7.9368 GB
+Peak GPU Memory: 7.4226 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 | 2336462209024.0 | 122045790683136.0 | 24.1200 | 16.7622 | 59.658 | 7.457 | 4429185024.0 | 25975962206208.0 |
-| 1000 | 0.0808 | 3312.0 | 3184.0 | 1.1229 | 16.7657 | 59.646 | 7.456 | 2720.0 | 2992.0 |
-| 2000 | 0.1616 | 5248.0 | 4048.0 | 1.2528 | 16.7825 | 59.586 | 7.448 | 5408.0 | 9984.0 |
-| 3000 | 0.2424 | 5600.0 | 3744.0 | 1.2812 | 16.7695 | 59.632 | 7.454 | 5312.0 | 23680.0 |
-| 4000 | 0.3232 | 5408.0 | 3920.0 | 1.2832 | 16.8694 | 59.279 | 7.41 | 5440.0 | 33280.0 |
-| 5000 | 0.4040 | 5376.0 | 3952.0 | 1.2841 | 16.7361 | 59.751 | 7.469 | 5408.0 | 27008.0 |
-| 6000 | 0.4848 | 5344.0 | 3680.0 | 1.2770 | 16.7635 | 59.653 | 7.457 | 5440.0 | 29312.0 |
-| 7000 | 0.5657 | 5024.0 | 3760.0 | 1.2800 | 16.7492 | 59.704 | 7.463 | 5184.0 | 39936.0 |
-| 8000 | 0.6465 | 4992.0 | 3712.0 | 1.2922 | 16.7445 | 59.721 | 7.465 | 5088.0 | 26752.0 |
-| 9000 | 0.7273 | 5056.0 | 3696.0 | 1.3042 | 16.773 | 59.62 | 7.452 | 4672.0 | 29312.0 |
-| 10000 | 0.8081 | 5824.0 | 3648.0 | 1.3192 | 16.7669 | 59.641 | 7.455 | 5312.0 | 24448.0 |
-| 11000 | 0.8889 | 5568.0 | 3872.0 | 1.3215 | 16.8215 | 59.448 | 7.431 | 5504.0 | 40704.0 |
-| 12000 | 0.9697 | 5440.0 | 3792.0 | 1.3263 | 16.7825 | 59.586 | 7.448 | 5120.0 | 72704.0 |
-| 12375 | 1.0 | 5696.0 | 3936.0 | 1.3389 | 16.7852 | 59.576 | 7.447 | 5696.0 | 40192.0 |
+| 0 | 0 | 1408749273088.0 | 96207267430400.0 | 20.4380 | 16.6447 | 60.079 | 7.51 | 7482638336.0 | 43430709297152.0 |
+| 1000 | 0.0404 | 1408.0 | 1432.0 | 0.8546 | 16.7128 | 59.835 | 7.479 | 788.0 | 1056.0 |
+| 2000 | 0.0808 | 988.0 | 928.0 | 0.7631 | 16.6827 | 59.942 | 7.493 | 520.0 | 302.0 |
+| 3000 | 0.1212 | 836.0 | 760.0 | 0.7155 | 16.633 | 60.121 | 7.515 | 402.0 | 196.0 |
+| 4000 | 0.1616 | 732.0 | 676.0 | 0.6800 | 16.6836 | 59.939 | 7.492 | 378.0 | 157.0 |
+| 5000 | 0.2020 | 676.0 | 668.0 | 0.6574 | 16.6514 | 60.055 | 7.507 | 322.0 | 227.0 |
+| 6000 | 0.2424 | 648.0 | 732.0 | 0.6383 | 16.6833 | 59.94 | 7.493 | 286.0 | 190.0 |
+| 7000 | 0.2828 | 612.0 | 632.0 | 0.6373 | 16.8106 | 59.486 | 7.436 | 286.0 | 169.0 |
+| 8000 | 0.3232 | 588.0 | 704.0 | 0.6243 | 16.6588 | 60.028 | 7.504 | 266.0 | 596.0 |
+| 9000 | 0.3636 | 560.0 | 644.0 | 0.6086 | 16.7587 | 59.67 | 7.459 | 284.0 | 488.0 |
+| 10000 | 0.4040 | 532.0 | 564.0 | 0.5994 | 16.6696 | 59.989 | 7.499 | 256.0 | 142.0 |
+| 11000 | 0.4444 | 544.0 | 628.0 | 0.5916 | 16.7004 | 59.879 | 7.485 | 252.0 | 153.0 |
+| 12000 | 0.4848 | 540.0 | 612.0 | 0.5828 | 16.7602 | 59.665 | 7.458 | 252.0 | 568.0 |
+| 13000 | 0.5253 | 528.0 | 612.0 | 0.5735 | 16.6596 | 60.025 | 7.503 | 260.0 | 160.0 |
+| 14000 | 0.5657 | 528.0 | 576.0 | 0.5628 | 16.7207 | 59.806 | 7.476 | 246.0 | 250.0 |
+| 15000 | 0.6061 | 478.0 | 524.0 | 0.5511 | 16.736 | 59.752 | 7.469 | 232.0 | 170.0 |
+| 16000 | 0.6465 | 442.0 | 552.0 | 0.5270 | 16.7225 | 59.8 | 7.475 | 228.0 | 214.0 |
+| 17000 | 0.6869 | 420.0 | 524.0 | 0.4692 | 16.6506 | 60.058 | 7.507 | 212.0 | 174.0 |
+| 18000 | 0.7273 | 384.0 | 478.0 | 0.4115 | 16.7225 | 59.8 | 7.475 | 208.0 | 144.0 |
+| 19000 | 0.7677 | 362.0 | 400.0 | 0.3610 | 16.6691 | 59.991 | 7.499 | 195.0 | 128.0 |
+| 20000 | 0.8081 | 344.0 | 346.0 | 0.3370 | 16.6695 | 59.99 | 7.499 | 184.0 | 107.5 |
+| 21000 | 0.8485 | 306.0 | 302.0 | 0.3061 | 16.7054 | 59.861 | 7.483 | 161.0 | 110.5 |
+| 22000 | 0.8889 | 300.0 | 318.0 | 0.2974 | 16.6709 | 59.985 | 7.498 | 160.0 | 84.0 |
+| 23000 | 0.9293 | 290.0 | 298.0 | 0.2890 | 16.7049 | 59.863 | 7.483 | 162.0 | 103.0 |
+| 24000 | 0.9697 | 300.0 | 290.0 | 0.2970 | 16.6771 | 59.963 | 7.495 | 164.0 | 85.5 |
+| 24750 | 1.0 | 280.0 | 290.0 | 0.2782 | 16.74 | 59.737 | 7.467 | 162.0 | 91.5 |
 
 ### Framework versions
 - Distily 0.2.0

logs/dataset_subset=default, dataset_uri=distily_c4_multilingual_1M, learning_rate=0.0001, per_device_train_batch_size=4/events.out.tfevents.1724143970.02dbb11e2dcc

@@ -0,0 +1,3 @@
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+oid sha256:4c5f2d8b25dfeef10e710f50dd3b67c11b795b907fed8a1442f9bc2d6103ea7c
+size 312