Training in progress, step 61875
Browse files- README.md +6 -6
- config.json +1 -1
- generation_config.json +1 -1
- logs/attn_norm=layernorm, attn_projector=orthogonal, attn_weight=5, learning_rate=0.0002, per_device_train_batch_size=16, warmup_ratio=0/events.out.tfevents.1725195412.e3f806ea38c9 +3 -0
- logs/attn_norm=layernorm, attn_projector=orthogonal, attn_weight=5, learning_rate=0.0002, per_device_train_batch_size=16, warmup_ratio=0/events.out.tfevents.1725210146.e3f806ea38c9 +3 -0
- logs/attn_norm=layernorm_teacher_only, attn_projector=orthogonal, attn_weight=5, learning_rate=0.0002, per_device_train_batch_size=16, warmup_ratio=0/completed.flag +0 -0
- model.safetensors +1 -1
- training_args.bin +2 -2
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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<br/>
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# Train Dataset
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Trained on 521,
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- Num Samples: `990,000`
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- Subset: `20231101.en`
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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=
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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=
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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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# Framework Versions
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- Distily 0.4.1
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- Transformers 4.44.
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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# Resource Usage Comparison
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- VRAM Use: 15.6998 GB
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# Distillation (Teacher -> Student) Architecture Difference:
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<br/>
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# Train Dataset
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Trained on 521,346,447 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
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- Num Samples: `990,000`
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- Subset: `20231101.en`
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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=layernorm_teacher_only, projector=orthogonal))
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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=layernorm_teacher_only, projector=orthogonal))`
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- train_embeddings: `True`
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- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7fc354bdc1c0>`
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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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# Framework Versions
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- Distily 0.4.1
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- Transformers 4.44.1
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- Pytorch 2.4.0+cu121
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- Datasets 2.21.0
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config.json
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}
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},
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.
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"use_cache": true,
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"vocab_size": 50257
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}
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}
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},
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"torch_dtype": "bfloat16",
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"transformers_version": "4.44.1",
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"use_cache": true,
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"vocab_size": 50257
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}
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generation_config.json
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.44.
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}
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"_from_model_config": true,
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"bos_token_id": 50256,
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"eos_token_id": 50256,
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"transformers_version": "4.44.1"
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}
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logs/attn_norm=layernorm, attn_projector=orthogonal, attn_weight=5, learning_rate=0.0002, per_device_train_batch_size=16, warmup_ratio=0/events.out.tfevents.1725195412.e3f806ea38c9
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logs/attn_norm=layernorm, attn_projector=orthogonal, attn_weight=5, learning_rate=0.0002, per_device_train_batch_size=16, warmup_ratio=0/events.out.tfevents.1725210146.e3f806ea38c9
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logs/attn_norm=layernorm_teacher_only, attn_projector=orthogonal, attn_weight=5, learning_rate=0.0002, per_device_train_batch_size=16, warmup_ratio=0/completed.flag
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model.safetensors
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training_args.bin
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