Training in progress, step 61875
Browse files- README.md +7 -7
- config.json +1 -1
- generation_config.json +1 -1
- logs/attn_layer_mapper=layer-2, attn_loss_fn=raw_mse, attn_norm=None, attn_projector=orthogonal, max_grad_norm=100/events.out.tfevents.1724924255.e3f806ea38c9 +3 -0
- logs/attn_layer_mapper=layer-2, attn_loss_fn=raw_mse, attn_norm=batchnorm, attn_projector=orthogonal/completed.flag +0 -0
- logs/attn_layer_mapper=layer-2, attn_loss_fn=raw_mse, attn_norm=layernorm, attn_projector=orthogonal, max_grad_norm=100/events.out.tfevents.1724924157.e3f806ea38c9 +3 -0
- logs/attn_layer_mapper=layer-2, attn_loss_fn=raw_mse, attn_norm=layernorm, attn_projector=orthogonal/events.out.tfevents.1724924206.e3f806ea38c9 +3 -0
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
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@@ -76,7 +76,7 @@ Trained on 145,744,973 tokens from the [wikimedia/wikipedia](https://huggingface
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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=25.0, loss_fn=
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```
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# Hyperparameters
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- lr_scheduler_type: `cosine_with_min_lr`
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- lr_scheduler_warmup_ratio: `0.5`
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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=25.0, loss_fn=
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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: `None`
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- student_model_config: `None`
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- dataset_test_size: `0.01`
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- gradient_accumulation_steps: `1`
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- weight_decay: `0.0`
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- max_grad_norm: `
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- warmup_ratio: `0.5`
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- warmup_steps: `0`
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- gradient_checkpointing: `True`
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# Framework Versions
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- Distily 0.4.
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- Transformers 4.44.
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- Pytorch 2.
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- Datasets 2.21.0
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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=25.0, loss_fn=raw_mse, layer_mapper=layer-2, norm=batchnorm, projector=orthogonal))
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```
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# Hyperparameters
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- lr_scheduler_type: `cosine_with_min_lr`
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- lr_scheduler_warmup_ratio: `0.5`
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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=25.0, loss_fn=raw_mse, layer_mapper=layer-2, norm=batchnorm, projector=orthogonal))`
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- train_embeddings: `True`
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- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7f4f563013f0>`
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- student_model_name_or_path: `None`
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- student_config_name_or_path: `None`
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- student_model_config: `None`
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- dataset_test_size: `0.01`
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- gradient_accumulation_steps: `1`
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- weight_decay: `0.0`
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- max_grad_norm: `1.0`
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- warmup_ratio: `0.5`
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- warmup_steps: `0`
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- gradient_checkpointing: `True`
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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_layer_mapper=layer-2, attn_loss_fn=raw_mse, attn_norm=None, attn_projector=orthogonal, max_grad_norm=100/events.out.tfevents.1724924255.e3f806ea38c9
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logs/attn_layer_mapper=layer-2, attn_loss_fn=raw_mse, attn_norm=batchnorm, attn_projector=orthogonal/completed.flag
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logs/attn_layer_mapper=layer-2, attn_loss_fn=raw_mse, attn_norm=layernorm, attn_projector=orthogonal, max_grad_norm=100/events.out.tfevents.1724924157.e3f806ea38c9
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logs/attn_layer_mapper=layer-2, attn_loss_fn=raw_mse, attn_norm=layernorm, attn_projector=orthogonal/events.out.tfevents.1724924206.e3f806ea38c9
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model.safetensors
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training_args.bin
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