lapp0 commited on
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End of training

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README.md CHANGED
@@ -16,14 +16,14 @@ This student model is distilled from the teacher model [gpt2](https://huggingfac
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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: 84.5
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- - eval_frwikippl: 356.0
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- - eval_zhwikippl: 135.0
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- - eval_tinystoriesppl: 72.0
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- - eval_loss: 0.6795
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- - eval_runtime: 16.7299
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- - eval_samples_per_second: 59.773
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- - eval_steps_per_second: 7.472
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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.
@@ -48,8 +48,8 @@ More information needed
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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: 0.0001
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- - train_batch_size: 4
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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
@@ -58,38 +58,26 @@ The following hyperparameters were used during training:
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  - num_epochs: 1.0
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  ### Resource Usage
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- Peak GPU Memory: 7.4226 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** | | 43.75 | 61.75 | | | | | 11.8125 | 19.125 |
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- | 0 | 0 | 3126736191488.0 | 129742372077568.0 | 20.7540 | 16.7407 | 59.735 | 7.467 | 6677331968.0 | 80264348827648.0 |
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- | 1000 | 0.0404 | 320.0 | 1504.0 | 1.5025 | 16.7846 | 59.579 | 7.447 | 245.0 | 280.0 |
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- | 2000 | 0.0808 | 220.0 | 800.0 | 1.3040 | 16.7756 | 59.61 | 7.451 | 189.0 | 201.0 |
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- | 3000 | 0.1212 | 180.0 | 648.0 | 1.1450 | 16.7863 | 59.572 | 7.447 | 153.0 | 149.0 |
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- | 4000 | 0.1616 | 148.0 | 552.0 | 1.0301 | 16.7242 | 59.794 | 7.474 | 121.5 | 153.0 |
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- | 5000 | 0.2020 | 129.0 | 452.0 | 0.9348 | 16.7817 | 59.589 | 7.449 | 105.0 | 176.0 |
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- | 6000 | 0.2424 | 115.5 | 442.0 | 0.8587 | 16.8358 | 59.397 | 7.425 | 86.0 | 139.0 |
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- | 7000 | 0.2828 | 103.0 | 432.0 | 0.8002 | 16.7689 | 59.634 | 7.454 | 78.5 | 139.0 |
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- | 8000 | 0.3232 | 96.5 | 418.0 | 0.7424 | 16.7778 | 59.602 | 7.45 | 73.5 | 126.0 |
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- | 9000 | 0.3636 | 84.5 | 356.0 | 0.6795 | 16.7299 | 59.773 | 7.472 | 72.0 | 135.0 |
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- | 10000 | 0.4040 | 81.5 | 304.0 | 0.6324 | 16.7186 | 59.813 | 7.477 | 66.0 | 125.5 |
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- | 11000 | 0.4444 | 77.5 | 282.0 | 0.5972 | 16.777 | 59.605 | 7.451 | 59.25 | 121.5 |
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- | 12000 | 0.4848 | 72.5 | 288.0 | 0.5723 | 16.7347 | 59.756 | 7.47 | 56.75 | 118.0 |
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- | 13000 | 0.5253 | 69.5 | 256.0 | 0.5577 | 16.7525 | 59.693 | 7.462 | 55.5 | 141.0 |
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- | 14000 | 0.5657 | 68.5 | 237.0 | 0.5389 | 16.7317 | 59.767 | 7.471 | 54.75 | 286.0 |
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- | 15000 | 0.6061 | 67.5 | 252.0 | 0.5187 | 16.7326 | 59.764 | 7.47 | 52.25 | 98.5 |
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- | 16000 | 0.6465 | 69.0 | 235.0 | 0.5174 | 16.8095 | 59.49 | 7.436 | 54.75 | 125.5 |
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- | 17000 | 0.6869 | 67.0 | 231.0 | 0.5048 | 16.7326 | 59.764 | 7.47 | 50.5 | 116.0 |
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- | 18000 | 0.7273 | 66.0 | 225.0 | 0.4909 | 16.7575 | 59.675 | 7.459 | 49.75 | 132.0 |
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- | 19000 | 0.7677 | 66.5 | 247.0 | 0.4894 | 16.8313 | 59.413 | 7.427 | 49.75 | 112.0 |
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- | 20000 | 0.8081 | 66.5 | 233.0 | 0.4870 | 16.7365 | 59.75 | 7.469 | 51.5 | 103.5 |
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- | 21000 | 0.8485 | 65.0 | 221.0 | 0.4831 | 16.703 | 59.869 | 7.484 | 50.75 | 181.0 |
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- | 22000 | 0.8889 | 65.5 | 199.0 | 0.4740 | 16.7629 | 59.656 | 7.457 | 49.5 | 95.5 |
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- | 23000 | 0.9293 | 67.0 | 223.0 | 0.4752 | 16.7201 | 59.808 | 7.476 | 46.5 | 174.0 |
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- | 24000 | 0.9697 | 65.0 | 207.0 | 0.4700 | 16.8026 | 59.515 | 7.439 | 46.75 | 98.5 |
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- | 24750 | 1.0 | 67.0 | 207.0 | 0.4672 | 16.7876 | 59.568 | 7.446 | 47.0 | 185.0 |
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  ### Framework versions
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  - Distily 0.2.0
 
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  The [Distily](https://github.com/lapp0/distily) library was used for this distillation.
17
 
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  It achieves the following results on the evaluation set:
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+ - eval_enwikippl: 2192.0
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+ - eval_frwikippl: 11200.0
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+ - eval_zhwikippl: 93184.0
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+ - eval_tinystoriesppl: 1808.0
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+ - eval_loss: 2.6293
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+ - eval_runtime: 16.9228
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+ - eval_samples_per_second: 59.092
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+ - eval_steps_per_second: 7.386
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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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  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: 0.0004
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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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  - num_epochs: 1.0
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  ### Resource Usage
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+ Peak GPU Memory: 7.9368 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** | | 43.75 | 61.75 | | | | | 11.8125 | 19.125 |
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+ | 0 | 0 | 2473901162496.0 | 170424302305280.0 | 20.7680 | 16.794 | 59.545 | 7.443 | 4060086272.0 | 71468255805440.0 |
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+ | 1000 | 0.0808 | 688.0 | 3728.0 | 1.9530 | 16.821 | 59.449 | 7.431 | 652.0 | 2784.0 |
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+ | 2000 | 0.1616 | 1728.0 | 8256.0 | 2.4948 | 16.7878 | 59.567 | 7.446 | 1384.0 | 35584.0 |
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+ | 3000 | 0.2424 | 2040.0 | 10112.0 | 2.6087 | 16.7522 | 59.694 | 7.462 | 1720.0 | 64256.0 |
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+ | 4000 | 0.3232 | 2160.0 | 9280.0 | 2.6353 | 16.796 | 59.538 | 7.442 | 1816.0 | 57088.0 |
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+ | 5000 | 0.4040 | 1904.0 | 9088.0 | 2.5782 | 16.8206 | 59.451 | 7.431 | 1848.0 | 61440.0 |
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+ | 6000 | 0.4848 | 1840.0 | 8960.0 | 2.5344 | 16.7618 | 59.659 | 7.457 | 1592.0 | 69120.0 |
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+ | 7000 | 0.5657 | 1808.0 | 8512.0 | 2.5269 | 16.7913 | 59.555 | 7.444 | 1648.0 | 60672.0 |
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+ | 8000 | 0.6465 | 2096.0 | 8960.0 | 2.6404 | 16.8233 | 59.442 | 7.43 | 1928.0 | 137216.0 |
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+ | 9000 | 0.7273 | 2192.0 | 11200.0 | 2.6293 | 16.9228 | 59.092 | 7.386 | 1808.0 | 93184.0 |
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+ | 10000 | 0.8081 | 1944.0 | 9984.0 | 2.5759 | 16.857 | 59.323 | 7.415 | 1568.0 | 80896.0 |
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+ | 11000 | 0.8889 | 1736.0 | 9344.0 | 2.5147 | 16.8438 | 59.369 | 7.421 | 1488.0 | 48640.0 |
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+ | 12000 | 0.9697 | 2224.0 | 11840.0 | 2.6633 | 16.7839 | 59.581 | 7.448 | 1968.0 | 98816.0 |
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+ | 12375 | 1.0 | 2432.0 | 11072.0 | 2.7197 | 16.7952 | 59.541 | 7.443 | 2176.0 | 109568.0 |
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Distily 0.2.0
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