| # Define the parameters | |
| model_name="gpt2-small" | |
| tok_name="gpt2" | |
| batch_size=10 | |
| max_tokens=500000000 | |
| sae_name="topk_transcoder" | |
| lr=0.0001 | |
| expansion_factor=32 | |
| k=32 | |
| auxk=256 | |
| auxk_coef=0.03125 | |
| device_id=7 | |
| max_epochs=1 | |
| dead_tokens_threshold=10000000 | |
| log_every_n_steps=50 | |
| use_loss_var=true | |
| num_workers=63 | |
| cd .. | |
| # Loop over 12 layers | |
| for layer in {0..11} | |
| do | |
| input_hook="blocks.${layer}.ln2.hook_normalized" | |
| output_hook="blocks.${layer}.hook_mlp_out" | |
| python Train_Transcoder.py \ | |
| --model_name "$model_name" \ | |
| --tok_name "$tok_name" \ | |
| --layer "$layer" \ | |
| --batch_size "$batch_size" \ | |
| --input_hook "$input_hook" \ | |
| --output_hook "$output_hook" \ | |
| --sae_name "$sae_name" \ | |
| --lr "$lr" \ | |
| --expansion_factor "$expansion_factor" \ | |
| --k "$k" \ | |
| --auxk "$auxk" \ | |
| --device_id "$device_id" \ | |
| --max_epochs "$max_epochs" \ | |
| --dead_tokens_threshold "$dead_tokens_threshold" \ | |
| --log_every_n_steps "$log_every_n_steps" \ | |
| --use_loss_var "$use_loss_var" \ | |
| --max_tokens "$max_tokens" \ | |
| --auxk_coef "$auxk_coef" \ | |
| --num_workers "$num_workers" | |
| done |