End of training

README.md

@@ -16,13 +16,13 @@ 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: 1360.0
-- eval_frwikippl: 5600.0
-- eval_zhwikippl: 132096.0
-- eval_tinystoriesppl: 904.0
-- eval_loss: 3.0667
-- eval_runtime: 12.9338
-- eval_samples_per_second: 46.39
+- eval_enwikippl: 1376.0
+- eval_frwikippl: 5856.0
+- eval_zhwikippl: 111104.0
+- eval_tinystoriesppl: 964.0
+- eval_loss: 3.1072
+- eval_runtime: 12.9331
+- eval_samples_per_second: 46.392
 - eval_steps_per_second: 11.598
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -46,7 +46,7 @@ More information needed
 ### 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=all, projector=None), attn_loss_component=LossComponent(label=attn, weight=0, loss_fn=None, layer_mapper=None, projector=None))
+- 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=last, 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
@@ -64,17 +64,17 @@ Peak GPU Memory: 8.0905 GB
 | 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 | 12.9195 | 46.441 | 11.61 | 12079595520.0 | 98956046499840.0 |
-| 750 | 0.1010 | 1360.0 | 5600.0 | 3.0667 | 12.9338 | 46.39 | 11.598 | 904.0 | 132096.0 |
-| 1500 | 0.2020 | 584.0 | 3600.0 | 2.2210 | 12.9258 | 46.419 | 11.605 | 444.0 | 968.0 |
-| 2250 | 0.3030 | 382.0 | 2024.0 | 1.9283 | 12.9374 | 46.377 | 11.594 | 290.0 | 372.0 |
-| 3000 | 0.4040 | 268.0 | 1088.0 | 1.6657 | 12.9348 | 46.387 | 11.597 | 230.0 | 204.0 |
-| 3750 | 0.5051 | 208.0 | 732.0 | 1.4758 | 12.9387 | 46.372 | 11.593 | 174.0 | 218.0 |
-| 4500 | 0.6061 | 169.0 | 564.0 | 1.2952 | 13.0113 | 46.114 | 11.528 | 145.0 | 142.0 |
-| 5250 | 0.7071 | 137.0 | 482.0 | 1.1321 | 12.9425 | 46.359 | 11.59 | 111.0 | 139.0 |
-| 6000 | 0.8081 | 125.0 | 448.0 | 1.0644 | 13.0023 | 46.146 | 11.536 | 100.5 | 123.5 |
-| 6750 | 0.9091 | 120.0 | 434.0 | 1.0300 | 12.9661 | 46.274 | 11.569 | 96.5 | 119.0 |
-| 7425 | 1.0 | 119.0 | 430.0 | 1.0247 | 13.1477 | 45.635 | 11.409 | 95.0 | 118.0 |
+| 0 | 0 | 1821066133504.0 | 158329674399744.0 | 20.2008 | 12.9107 | 46.473 | 11.618 | 12079595520.0 | 98956046499840.0 |
+| 750 | 0.1010 | 1376.0 | 5856.0 | 3.1072 | 12.9331 | 46.392 | 11.598 | 964.0 | 111104.0 |
+| 1500 | 0.2020 | 580.0 | 3600.0 | 2.2189 | 12.9266 | 46.416 | 11.604 | 438.0 | 1020.0 |
+| 2250 | 0.3030 | 376.0 | 1904.0 | 1.9249 | 12.9295 | 46.405 | 11.601 | 312.0 | 374.0 |
+| 3000 | 0.4040 | 268.0 | 1080.0 | 1.6655 | 12.9091 | 46.479 | 11.62 | 238.0 | 208.0 |
+| 3750 | 0.5051 | 211.0 | 732.0 | 1.4810 | 12.9336 | 46.391 | 11.598 | 172.0 | 217.0 |
+| 4500 | 0.6061 | 167.0 | 580.0 | 1.2985 | 12.9202 | 46.439 | 11.61 | 143.0 | 146.0 |
+| 5250 | 0.7071 | 135.0 | 486.0 | 1.1339 | 12.9225 | 46.431 | 11.608 | 112.5 | 133.0 |
+| 6000 | 0.8081 | 124.5 | 452.0 | 1.0647 | 12.9107 | 46.473 | 11.618 | 101.5 | 125.5 |
+| 6750 | 0.9091 | 118.5 | 436.0 | 1.0324 | 12.9153 | 46.456 | 11.614 | 97.5 | 120.0 |
+| 7425 | 1.0 | 117.5 | 432.0 | 1.0264 | 13.1576 | 45.601 | 11.4 | 95.5 | 118.5 |
 
 ### Framework versions
 - Distily 0.2.0

logs/hs_layer_mapper=last, hs_loss_fn=cos, hs_weight=1.0/events.out.tfevents.1724122712.f383272e719b

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