End of training
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README.md
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# Resource Usage Comparison
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- VRAM Use: 15.
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# Distillation (Teacher -> Student) Architecture Difference:
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# Training Objective
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```
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DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5, loss_fn=raw_mse, layer_mapper=layer-2, norm=instance_teacher_only, projector=
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```
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# Hyperparameters
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- optimizer: `Adam with betas=(0.9,0.999) and epsilon=1e-08`
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- lr_scheduler_type: `polynomial`
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- num_epochs: `1.0`
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- distillation_objective: `DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5, loss_fn=raw_mse, layer_mapper=layer-2, norm=instance_teacher_only, projector=
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- train_embeddings: `True`
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- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at
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- student_model_name_or_path: `None`
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- student_config_name_or_path: `distilbert/distilgpt2`
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- student_model_config: `None`
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- Distily 0.4.1
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu121
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- Datasets 2.
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# Resource Usage Comparison
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- VRAM Use: 15.6974 GB
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# Distillation (Teacher -> Student) Architecture Difference:
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# Training Objective
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```
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DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5, loss_fn=raw_mse, layer_mapper=layer-2, norm=instance_teacher_only, projector=mlp))
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```
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# Hyperparameters
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- optimizer: `Adam with betas=(0.9,0.999) and epsilon=1e-08`
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- lr_scheduler_type: `polynomial`
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- num_epochs: `1.0`
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- distillation_objective: `DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5, loss_fn=raw_mse, layer_mapper=layer-2, norm=instance_teacher_only, projector=mlp))`
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- train_embeddings: `True`
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- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7f460c9e5c00>`
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- student_model_name_or_path: `None`
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- student_config_name_or_path: `distilbert/distilgpt2`
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- student_model_config: `None`
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- Distily 0.4.1
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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logs/attn_norm=instance_teacher_only, attn_projector=mlp, attn_weight=5, learning_rate=0.0001, per_device_train_batch_size=16, warmup_ratio=0/events.out.tfevents.1725254166.cfb07cadeb51
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model.safetensors
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training_args.bin
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