Training in progress, step 61875
Browse files- README.md +32 -32
- logs/attn_loss_fn=mse, attn_weight=10.0, hs_loss_fn=raw_mse, hs_weight=10.0, learning_rate=0.004, warmup_ratio=0.1/events.out.tfevents.1723776807.93d6cbb3ad53 +3 -0
- logs/attn_loss_fn=mse, attn_weight=10.0, hs_loss_fn=raw_mse, hs_weight=10.0, learning_rate=0.004, warmup_ratio=0/events.out.tfevents.1723776606.93d6cbb3ad53 +2 -2
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
CHANGED
@@ -15,14 +15,14 @@ This student model is distilled from the teacher model [roneneldan/TinyStories-3
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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:
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- eval_frwikippl:
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- eval_zhwikippl:
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- eval_tinystoriesppl:
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- eval_loss:
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- eval_runtime:
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- eval_samples_per_second:
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- eval_steps_per_second: 9.
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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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@@ -47,7 +47,7 @@ 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=10.0, loss_fn=raw_mse, layer_mapper=None, projector=None), attn_loss_component=LossComponent(label=attn, weight=10.0, loss_fn=mse, layer_mapper=None, projector=None))
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- train_embeddings: True
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- learning_rate: 0.
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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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@@ -62,31 +62,31 @@ Peak GPU Memory: 8.2666 GB
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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 |
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| 3000 | 0.0485 |
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| 6000 | 0.0970 |
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| 9000 | 0.1455 |
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| 12000 | 0.1939 |
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| 15000 | 0.2424 |
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| 18000 | 0.2909 |
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| 21000 | 0.3394 |
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| 24000 | 0.3879 |
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| 27000 | 0.4364 |
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| 30000 | 0.4848 |
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| 33000 | 0.5333 |
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| 36000 | 0.5818 |
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| 39000 | 0.6303 |
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| 42000 | 0.6788 |
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| 45000 | 0.7273 |
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| 48000 | 0.7758 |
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| 51000 | 0.8242 |
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| 54000 | 0.8727 |
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| 57000 | 0.9212 |
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| 60000 | 0.9697 |
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| 61875 | 1.0 |
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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.
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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: 149.5442
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- eval_frwikippl: 28142.1230
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- eval_zhwikippl: 243104.3594
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- eval_tinystoriesppl: 11.2706
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- eval_loss: 7.4452
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- eval_runtime: 66.0052
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- eval_samples_per_second: 75.752
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- eval_steps_per_second: 9.469
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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=10.0, loss_fn=raw_mse, layer_mapper=None, projector=None), attn_loss_component=LossComponent(label=attn, weight=10.0, loss_fn=mse, layer_mapper=None, projector=None))
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- train_embeddings: True
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- learning_rate: 0.004
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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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| 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 | 58069.8203 | 77442.5625 | 18.5372 | 65.9335 | 75.834 | 9.479 | 46072.8867 | 100550.5078 |
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| 3000 | 0.0485 | 145.3919 | 28068.8965 | 7.4450 | 66.1007 | 75.642 | 9.455 | 10.8792 | 239563.0469 |
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| 6000 | 0.0970 | 143.8738 | 27934.7852 | 7.4443 | 65.9587 | 75.805 | 9.476 | 10.7017 | 239818.8281 |
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| 9000 | 0.1455 | 149.5442 | 28142.1230 | 7.4452 | 66.0052 | 75.752 | 9.469 | 11.2706 | 243104.3594 |
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| 12000 | 0.1939 | 141.4481 | 28096.5879 | 7.4447 | 66.228 | 75.497 | 9.437 | 10.4616 | 242650.5938 |
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| 15000 | 0.2424 | 141.9365 | 27532.4258 | 7.4447 | 66.1198 | 75.62 | 9.453 | 10.5402 | 235884.5 |
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| 18000 | 0.2909 | 150.4271 | 28453.0332 | 7.4452 | 65.9158 | 75.854 | 9.482 | 11.3604 | 248415.0781 |
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| 21000 | 0.3394 | 148.4649 | 27337.2715 | 7.4450 | 65.7078 | 76.094 | 9.512 | 11.2888 | 229674.3125 |
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| 24000 | 0.3879 | 149.7760 | 28039.2520 | 7.4446 | 65.7891 | 76.0 | 9.5 | 11.2827 | 240716.3594 |
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| 27000 | 0.4364 | 141.8706 | 28049.1211 | 7.4454 | 65.831 | 75.952 | 9.494 | 10.5280 | 235255.9062 |
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| 30000 | 0.4848 | 144.7906 | 28084.7207 | 7.4449 | 65.9422 | 75.824 | 9.478 | 10.7119 | 240716.3594 |
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| 33000 | 0.5333 | 149.6832 | 28237.4258 | 7.4454 | 65.807 | 75.98 | 9.497 | 11.2524 | 244013.9531 |
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| 36000 | 0.5818 | 148.6030 | 27445.3125 | 7.4453 | 65.6651 | 76.144 | 9.518 | 11.2729 | 236893.5625 |
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| 39000 | 0.6303 | 142.9683 | 27676.2949 | 7.4447 | 65.6729 | 76.135 | 9.517 | 10.6589 | 235381.5781 |
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| 42000 | 0.6788 | 146.5510 | 27895.4648 | 7.4449 | 65.6881 | 76.117 | 9.515 | 10.9904 | 239690.7812 |
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| 45000 | 0.7273 | 149.2144 | 28023.4531 | 7.4454 | 65.9058 | 75.866 | 9.483 | 11.2701 | 240716.3594 |
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| 48000 | 0.7758 | 144.2086 | 28243.4043 | 7.4449 | 65.873 | 75.904 | 9.488 | 10.7022 | 244339.7188 |
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| 51000 | 0.8242 | 141.9915 | 27781.7559 | 7.4450 | 65.9256 | 75.843 | 9.48 | 10.5589 | 239563.0469 |
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| 54000 | 0.8727 | 145.6399 | 28219.5234 | 7.4451 | 65.6892 | 76.116 | 9.515 | 10.8693 | 238542.6094 |
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| 57000 | 0.9212 | 144.2365 | 27040.4609 | 7.4445 | 65.6838 | 76.122 | 9.515 | 10.8312 | 227175.6875 |
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| 60000 | 0.9697 | 144.3482 | 26979.5938 | 7.4447 | 65.623 | 76.193 | 9.524 | 10.9257 | 232138.6562 |
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| 61875 | 1.0 | 146.9147 | 28084.7207 | 7.4450 | 65.6082 | 76.21 | 9.526 | 10.9569 | 237146.5 |
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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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logs/attn_loss_fn=mse, attn_weight=10.0, hs_loss_fn=raw_mse, hs_weight=10.0, learning_rate=0.004, warmup_ratio=0.1/events.out.tfevents.1723776807.93d6cbb3ad53
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model.safetensors
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