End of training

README.md

@@ -78,7 +78,7 @@ GPT2LMHeadModel(
 
 # Resource Usage
 
-- Max Train VRAM Use: 15.7128 GB
+- Max Train VRAM Use: 15.7120 GB
 - Available VRAM: 23.6429 GB
 - GPUs: 
   - 1x NVIDIA GeForce RTX 4090
@@ -115,7 +115,7 @@ GPT2LMHeadModel(
 <br/>
 
 # Train Dataset
-Trained on 521,413,804 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
+Trained on 521,332,238 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
 
 - Num Samples: `990,000`
 - Subset: `20231101.en`
@@ -125,7 +125,7 @@ Trained on 521,413,804 tokens from the [wikimedia/wikipedia](https://huggingface
 # Training 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_affine, projector=orthogonal))
+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_affine, projector=mlp_64_l2))
 ```
 
 # Hyperparameters
@@ -141,8 +141,8 @@ The following hyperparameters were used during training:
 - optimizer: `Adam with betas=(0.9,0.999) and epsilon=1e-08`
 - lr_scheduler_type: `polynomial`
 - num_epochs: `1.0`
-- 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_affine, projector=orthogonal))`
-- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7f5b3de02770>`
+- 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_affine, projector=mlp_64_l2))`
+- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7f714ea4b430>`
 - student_model_name_or_path: `None`
 - student_config_name_or_path: `distilbert/distilgpt2`
 - student_model_config: `None`

logs/attn_norm=layernorm_teacher_only_affine, attn_projector=mlp_64_l2, attn_weight=5, learning_rate=0.0002, per_device_train_batch_size=16, warmup_ratio=0/events.out.tfevents.1725543099.a7e428977e35

@@ -0,0 +1,3 @@
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+size 529