| + deepspeed --master_port 36630 --module safe_rlhf.finetune --train_datasets inverse-json::/home/hansirui_1st/jiayi/resist/imdb_data/train/neg/500/train.json --model_name_or_path /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000 --max_length 512 --trust_remote_code True --epochs 1 --per_device_train_batch_size 1 --per_device_eval_batch_size 4 --gradient_accumulation_steps 8 --gradient_checkpointing --learning_rate 1e-5 --lr_warmup_ratio 0 --weight_decay 0.0 --lr_scheduler_type constant --weight_decay 0.0 --seed 42 --output_dir /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000-Q2-500 --log_type wandb --log_run_name imdb-tinyllama-3T-s3-Q1-2000-Q2-500 --log_project Inverse_Alignment_IMDb --zero_stage 3 --offload none --bf16 True --tf32 True --save_16bit |
| nvcc warning : incompatible redefinition for option |
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| [rank5]:[W527 21:10:02.651466586 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 5] using GPU 5 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
| [rank3]:[W527 21:10:03.695994735 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 3] using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
| [rank2]:[W527 21:10:03.716807972 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 2] using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
| [rank4]:[W527 21:10:03.768185518 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 4] using GPU 4 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
| [rank6]:[W527 21:10:03.768223860 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 6] using GPU 6 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
| [rank7]:[W527 21:10:03.061055247 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 7] using GPU 7 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
| [rank0]:[W527 21:10:03.061103034 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 0] using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
| [rank1]:[W527 21:10:03.083403051 ProcessGroupNCCL.cpp:4561] [PG ID 0 PG GUID 0 Rank 1] using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if this rank to GPU mapping is incorrect. Specify device_ids in barrier() to force use of a particular device, or call init_process_group() with a device_id. |
| loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/config.json |
| loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/config.json |
| loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/config.json |
| loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/config.json |
| loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/config.json |
| loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/config.json |
| loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/config.json |
| loading configuration file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/config.json |
| Model config LlamaConfig { |
| "architectures": [ |
| "LlamaForCausalLM" |
| ], |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "head_dim": 64, |
| "hidden_act": "silu", |
| "hidden_size": 2048, |
| "initializer_range": 0.02, |
| "intermediate_size": 5632, |
| "max_position_embeddings": 2048, |
| "mlp_bias": false, |
| "model_type": "llama", |
| "num_attention_heads": 32, |
| "num_hidden_layers": 22, |
| "num_key_value_heads": 4, |
| "pad_token_id": 32000, |
| "pretraining_tp": 1, |
| "rms_norm_eps": 1e-05, |
| "rope_scaling": null, |
| "rope_theta": 10000.0, |
| "tie_word_embeddings": false, |
| "torch_dtype": "float32", |
| "transformers_version": "4.52.1", |
| "use_cache": true, |
| "vocab_size": 32001 |
| } |
|
|
| Model config LlamaConfig { |
| "architectures": [ |
| "LlamaForCausalLM" |
| ], |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "head_dim": 64, |
| "hidden_act": "silu", |
| "hidden_size": 2048, |
| "initializer_range": 0.02, |
| "intermediate_size": 5632, |
| "max_position_embeddings": 2048, |
| "mlp_bias": false, |
| "model_type": "llama", |
| "num_attention_heads": 32, |
| "num_hidden_layers": 22, |
| "num_key_value_heads": 4, |
| "pad_token_id": 32000, |
| "pretraining_tp": 1, |
| "rms_norm_eps": 1e-05, |
| "rope_scaling": null, |
| "rope_theta": 10000.0, |
| "tie_word_embeddings": false, |
| "torch_dtype": "float32", |
| "transformers_version": "4.52.1", |
| "use_cache": true, |
| "vocab_size": 32001 |
| } |
|
|
| Model config LlamaConfig { |
| "architectures": [ |
| "LlamaForCausalLM" |
| ], |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "head_dim": 64, |
| "hidden_act": "silu", |
| "hidden_size": 2048, |
| "initializer_range": 0.02, |
| "intermediate_size": 5632, |
| "max_position_embeddings": 2048, |
| "mlp_bias": false, |
| "model_type": "llama", |
| "num_attention_heads": 32, |
| "num_hidden_layers": 22, |
| "num_key_value_heads": 4, |
| "pad_token_id": 32000, |
| "pretraining_tp": 1, |
| "rms_norm_eps": 1e-05, |
| "rope_scaling": null, |
| "rope_theta": 10000.0, |
| "tie_word_embeddings": false, |
| "torch_dtype": "float32", |
| "transformers_version": "4.52.1", |
| "use_cache": true, |
| "vocab_size": 32001 |
| } |
|
|
| Model config LlamaConfig { |
| "architectures": [ |
| "LlamaForCausalLM" |
| ], |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "head_dim": 64, |
| "hidden_act": "silu", |
| "hidden_size": 2048, |
| "initializer_range": 0.02, |
| "intermediate_size": 5632, |
| "max_position_embeddings": 2048, |
| "mlp_bias": false, |
| "model_type": "llama", |
| "num_attention_heads": 32, |
| "num_hidden_layers": 22, |
| "num_key_value_heads": 4, |
| "pad_token_id": 32000, |
| "pretraining_tp": 1, |
| "rms_norm_eps": 1e-05, |
| "rope_scaling": null, |
| "rope_theta": 10000.0, |
| "tie_word_embeddings": false, |
| "torch_dtype": "float32", |
| "transformers_version": "4.52.1", |
| "use_cache": true, |
| "vocab_size": 32001 |
| } |
|
|
| Model config LlamaConfig { |
| "architectures": [ |
| "LlamaForCausalLM" |
| ], |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "head_dim": 64, |
| "hidden_act": "silu", |
| "hidden_size": 2048, |
| "initializer_range": 0.02, |
| "intermediate_size": 5632, |
| "max_position_embeddings": 2048, |
| "mlp_bias": false, |
| "model_type": "llama", |
| "num_attention_heads": 32, |
| "num_hidden_layers": 22, |
| "num_key_value_heads": 4, |
| "pad_token_id": 32000, |
| "pretraining_tp": 1, |
| "rms_norm_eps": 1e-05, |
| "rope_scaling": null, |
| "rope_theta": 10000.0, |
| "tie_word_embeddings": false, |
| "torch_dtype": "float32", |
| "transformers_version": "4.52.1", |
| "use_cache": true, |
| "vocab_size": 32001 |
| } |
|
|
| Model config LlamaConfig { |
| "architectures": [ |
| "LlamaForCausalLM" |
| ], |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "head_dim": 64, |
| "hidden_act": "silu", |
| "hidden_size": 2048, |
| "initializer_range": 0.02, |
| "intermediate_size": 5632, |
| "max_position_embeddings": 2048, |
| "mlp_bias": false, |
| "model_type": "llama", |
| "num_attention_heads": 32, |
| "num_hidden_layers": 22, |
| "num_key_value_heads": 4, |
| "pad_token_id": 32000, |
| "pretraining_tp": 1, |
| "rms_norm_eps": 1e-05, |
| "rope_scaling": null, |
| "rope_theta": 10000.0, |
| "tie_word_embeddings": false, |
| "torch_dtype": "float32", |
| "transformers_version": "4.52.1", |
| "use_cache": true, |
| "vocab_size": 32001 |
| } |
|
|
| Model config LlamaConfig { |
| "architectures": [ |
| "LlamaForCausalLM" |
| ], |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "head_dim": 64, |
| "hidden_act": "silu", |
| "hidden_size": 2048, |
| "initializer_range": 0.02, |
| "intermediate_size": 5632, |
| "max_position_embeddings": 2048, |
| "mlp_bias": false, |
| "model_type": "llama", |
| "num_attention_heads": 32, |
| "num_hidden_layers": 22, |
| "num_key_value_heads": 4, |
| "pad_token_id": 32000, |
| "pretraining_tp": 1, |
| "rms_norm_eps": 1e-05, |
| "rope_scaling": null, |
| "rope_theta": 10000.0, |
| "tie_word_embeddings": false, |
| "torch_dtype": "float32", |
| "transformers_version": "4.52.1", |
| "use_cache": true, |
| "vocab_size": 32001 |
| } |
|
|
| Model config LlamaConfig { |
| "architectures": [ |
| "LlamaForCausalLM" |
| ], |
| "attention_bias": false, |
| "attention_dropout": 0.0, |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "head_dim": 64, |
| "hidden_act": "silu", |
| "hidden_size": 2048, |
| "initializer_range": 0.02, |
| "intermediate_size": 5632, |
| "max_position_embeddings": 2048, |
| "mlp_bias": false, |
| "model_type": "llama", |
| "num_attention_heads": 32, |
| "num_hidden_layers": 22, |
| "num_key_value_heads": 4, |
| "pad_token_id": 32000, |
| "pretraining_tp": 1, |
| "rms_norm_eps": 1e-05, |
| "rope_scaling": null, |
| "rope_theta": 10000.0, |
| "tie_word_embeddings": false, |
| "torch_dtype": "float32", |
| "transformers_version": "4.52.1", |
| "use_cache": true, |
| "vocab_size": 32001 |
| } |
|
|
| loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/pytorch_model.bin |
| loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/pytorch_model.bin |
| loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/pytorch_model.bin |
| Will use torch_dtype=torch.float32 as defined in model |
| Will use torch_dtype=torch.float32 as defined in model |
| Will use torch_dtype=torch.float32 as defined in model |
| Instantiating LlamaForCausalLM model under default dtype torch.float32. |
| Instantiating LlamaForCausalLM model under default dtype torch.float32. |
| Instantiating LlamaForCausalLM model under default dtype torch.float32. |
| loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/pytorch_model.bin |
| Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
| Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
| Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
| Will use torch_dtype=torch.float32 as defined in model |
| Instantiating LlamaForCausalLM model under default dtype torch.float32. |
| loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/pytorch_model.bin |
| Will use torch_dtype=torch.float32 as defined in model |
| loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/pytorch_model.bin |
| Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
| Instantiating LlamaForCausalLM model under default dtype torch.float32. |
| Will use torch_dtype=torch.float32 as defined in model |
| Instantiating LlamaForCausalLM model under default dtype torch.float32. |
| Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
| loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/pytorch_model.bin |
| Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
| Will use torch_dtype=torch.float32 as defined in model |
| Instantiating LlamaForCausalLM model under default dtype torch.float32. |
| Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
| loading weights file /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000/pytorch_model.bin |
| Will use torch_dtype=torch.float32 as defined in model |
| Instantiating LlamaForCausalLM model under default dtype torch.float32. |
| Detected DeepSpeed ZeRO-3: activating zero.init() for this model |
| Generate config GenerationConfig { |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "pad_token_id": 32000 |
| } |
|
|
| Generate config GenerationConfig { |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "pad_token_id": 32000 |
| } |
|
|
| Generate config GenerationConfig { |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "pad_token_id": 32000 |
| } |
|
|
| Generate config GenerationConfig { |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "pad_token_id": 32000 |
| } |
|
|
| Generate config GenerationConfig { |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "pad_token_id": 32000 |
| } |
|
|
| Generate config GenerationConfig { |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "pad_token_id": 32000 |
| } |
|
|
| Generate config GenerationConfig { |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "pad_token_id": 32000 |
| } |
|
|
| Generate config GenerationConfig { |
| "bos_token_id": 1, |
| "eos_token_id": 2, |
| "pad_token_id": 32000 |
| } |
|
|
| All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
| All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000. |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
| All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
| All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000. |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
| All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
| Generation config file not found, using a generation config created from the model config. |
| All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000. |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
| Generation config file not found, using a generation config created from the model config. |
| Generation config file not found, using a generation config created from the model config. |
| All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
| All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000. |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
| All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
| All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000. |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
| All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
| All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000. |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
| Generation config file not found, using a generation config created from the model config. |
| Generation config file not found, using a generation config created from the model config. |
| Generation config file not found, using a generation config created from the model config. |
| All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
| All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000. |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
| Generation config file not found, using a generation config created from the model config. |
| loading file tokenizer.model |
| loading file tokenizer.json |
| loading file added_tokens.json |
| loading file special_tokens_map.json |
| loading file tokenizer_config.json |
| loading file tokenizer.model |
| loading file chat_template.jinja |
| loading file tokenizer.json |
| loading file added_tokens.json |
| loading file special_tokens_map.json |
| loading file tokenizer_config.json |
| loading file chat_template.jinja |
| loading file tokenizer.model |
| loading file tokenizer.json |
| loading file added_tokens.json |
| loading file special_tokens_map.json |
| loading file tokenizer_config.json |
| loading file chat_template.jinja |
| loading file tokenizer.model |
| loading file tokenizer.json |
| loading file added_tokens.json |
| loading file special_tokens_map.json |
| loading file tokenizer_config.json |
| loading file chat_template.jinja |
| loading file tokenizer.model |
| loading file tokenizer.json |
| loading file added_tokens.json |
| loading file special_tokens_map.json |
| loading file tokenizer_config.json |
| loading file chat_template.jinja |
| loading file tokenizer.model |
| loading file tokenizer.json |
| loading file added_tokens.json |
| loading file special_tokens_map.json |
| loading file tokenizer_config.json |
| loading file chat_template.jinja |
| loading file tokenizer.model |
| loading file tokenizer.json |
| loading file added_tokens.json |
| loading file special_tokens_map.json |
| loading file tokenizer_config.json |
| loading file chat_template.jinja |
| All model checkpoint weights were used when initializing LlamaForCausalLM. |
|
|
| All the weights of LlamaForCausalLM were initialized from the model checkpoint at /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000. |
| If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training. |
| Generation config file not found, using a generation config created from the model config. |
| loading file tokenizer.model |
| loading file tokenizer.json |
| loading file added_tokens.json |
| loading file special_tokens_map.json |
| loading file tokenizer_config.json |
| loading file chat_template.jinja |
| Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
| Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
| Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
| Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root...Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
|
|
| Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
| Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
| Using /home/hansirui_1st/.cache/torch_extensions/py311_cu124 as PyTorch extensions root... |
| Detected CUDA files, patching ldflags |
| Emitting ninja build file /home/hansirui_1st/.cache/torch_extensions/py311_cu124/fused_adam/build.ninja... |
| /aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/torch/utils/cpp_extension.py:2059: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. |
| If this is not desired, please set os.environ[ |
| warnings.warn( |
| Building extension module fused_adam... |
| Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N) |
| Loading extension module fused_adam... |
| Loading extension module fused_adam...Loading extension module fused_adam... |
|
|
| Loading extension module fused_adam... |
| Loading extension module fused_adam... |
| Loading extension module fused_adam... |
| Loading extension module fused_adam... |
| Loading extension module fused_adam... |
| `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
| `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
| `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
| `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
| `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
| `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
| `use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
| wandb: Currently logged in as: xtom to https://api.wandb.ai. Use `wandb login --relogin` to force relogin |
| wandb: Tracking run with wandb version 0.19.11 |
| wandb: Run data is saved locally in /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000-Q2-500/wandb/run-20250527_211020-o4c4mal9 |
| wandb: Run `wandb offline` to turn off syncing. |
| wandb: Syncing run imdb-tinyllama-3T-s3-Q1-2000-Q2-500 |
| wandb: βοΈ View project at https://wandb.ai/xtom/Inverse_Alignment_IMDb |
| wandb: π View run at https://wandb.ai/xtom/Inverse_Alignment_IMDb/runs/o4c4mal9 |
|
Training 1/1 epoch: 0%| | 0/63 [00:00<?, ?it/s]`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`. |
|
Training 1/1 epoch (loss 2.7620): 0%| | 0/63 [00:09<?, ?it/s]
Training 1/1 epoch (loss 2.7620): 2%|β | 1/63 [00:09<09:38, 9.33s/it]
Training 1/1 epoch (loss 2.7506): 2%|β | 1/63 [00:11<09:38, 9.33s/it]
Training 1/1 epoch (loss 2.7506): 3%|β | 2/63 [00:11<05:23, 5.30s/it]
Training 1/1 epoch (loss 2.8071): 3%|β | 2/63 [00:13<05:23, 5.30s/it]
Training 1/1 epoch (loss 2.8071): 5%|β | 3/63 [00:13<03:26, 3.44s/it]
Training 1/1 epoch (loss 2.6323): 5%|β | 3/63 [00:14<03:26, 3.44s/it]
Training 1/1 epoch (loss 2.6323): 6%|β | 4/63 [00:14<02:30, 2.56s/it]
Training 1/1 epoch (loss 2.9069): 6%|β | 4/63 [00:14<02:30, 2.56s/it]
Training 1/1 epoch (loss 2.9069): 8%|β | 5/63 [00:14<01:50, 1.90s/it]
Training 1/1 epoch (loss 2.6182): 8%|β | 5/63 [00:16<01:50, 1.90s/it]
Training 1/1 epoch (loss 2.6182): 10%|β | 6/63 [00:16<01:44, 1.84s/it]
Training 1/1 epoch (loss 2.7018): 10%|β | 6/63 [00:18<01:44, 1.84s/it]
Training 1/1 epoch (loss 2.7018): 11%|β | 7/63 [00:18<01:41, 1.82s/it]
Training 1/1 epoch (loss 2.5820): 11%|β | 7/63 [00:19<01:41, 1.82s/it]
Training 1/1 epoch (loss 2.5820): 13%|ββ | 8/63 [00:19<01:34, 1.72s/it]
Training 1/1 epoch (loss 2.9575): 13%|ββ | 8/63 [00:21<01:34, 1.72s/it]
Training 1/1 epoch (loss 2.9575): 14%|ββ | 9/63 [00:21<01:23, 1.54s/it]
Training 1/1 epoch (loss 2.8644): 14%|ββ | 9/63 [00:21<01:23, 1.54s/it]
Training 1/1 epoch (loss 2.8644): 16%|ββ | 10/63 [00:21<01:04, 1.22s/it]
Training 1/1 epoch (loss 2.6631): 16%|ββ | 10/63 [00:23<01:04, 1.22s/it]
Training 1/1 epoch (loss 2.6631): 17%|ββ | 11/63 [00:23<01:14, 1.43s/it]
Training 1/1 epoch (loss 2.5904): 17%|ββ | 11/63 [00:25<01:14, 1.43s/it]
Training 1/1 epoch (loss 2.5904): 19%|ββ | 12/63 [00:25<01:20, 1.58s/it]
Training 1/1 epoch (loss 2.7764): 19%|ββ | 12/63 [00:25<01:20, 1.58s/it]
Training 1/1 epoch (loss 2.7764): 21%|ββ | 13/63 [00:25<01:03, 1.26s/it]
Training 1/1 epoch (loss 2.6447): 21%|ββ | 13/63 [00:28<01:03, 1.26s/it]
Training 1/1 epoch (loss 2.6447): 22%|βββ | 14/63 [00:28<01:14, 1.51s/it]
Training 1/1 epoch (loss 2.6905): 22%|βββ | 14/63 [00:29<01:14, 1.51s/it]
Training 1/1 epoch (loss 2.6905): 24%|βββ | 15/63 [00:29<01:06, 1.38s/it]
Training 1/1 epoch (loss 2.7075): 24%|βββ | 15/63 [00:29<01:06, 1.38s/it]
Training 1/1 epoch (loss 2.7075): 25%|βββ | 16/63 [00:29<00:54, 1.15s/it]
Training 1/1 epoch (loss 2.5917): 25%|βββ | 16/63 [00:30<00:54, 1.15s/it]
Training 1/1 epoch (loss 2.5917): 27%|βββ | 17/63 [00:30<00:53, 1.17s/it]
Training 1/1 epoch (loss 2.3245): 27%|βββ | 17/63 [00:33<00:53, 1.17s/it]
Training 1/1 epoch (loss 2.3245): 29%|βββ | 18/63 [00:33<01:09, 1.54s/it]
Training 1/1 epoch (loss 2.6253): 29%|βββ | 18/63 [00:33<01:09, 1.54s/it]
Training 1/1 epoch (loss 2.6253): 30%|βββ | 19/63 [00:33<00:54, 1.24s/it]
Training 1/1 epoch (loss 2.5850): 30%|βββ | 19/63 [00:35<00:54, 1.24s/it]
Training 1/1 epoch (loss 2.5850): 32%|ββββ | 20/63 [00:35<00:51, 1.20s/it]
Training 1/1 epoch (loss 2.6461): 32%|ββββ | 20/63 [00:37<00:51, 1.20s/it]
Training 1/1 epoch (loss 2.6461): 33%|ββββ | 21/63 [00:37<01:02, 1.49s/it]
Training 1/1 epoch (loss 2.6309): 33%|ββββ | 21/63 [00:37<01:02, 1.49s/it]
Training 1/1 epoch (loss 2.6309): 35%|ββββ | 22/63 [00:37<00:48, 1.19s/it]
Training 1/1 epoch (loss 2.7441): 35%|ββββ | 22/63 [00:39<00:48, 1.19s/it]
Training 1/1 epoch (loss 2.7441): 37%|ββββ | 23/63 [00:39<00:53, 1.33s/it]
Training 1/1 epoch (loss 2.5765): 37%|ββββ | 23/63 [00:40<00:53, 1.33s/it]
Training 1/1 epoch (loss 2.5765): 38%|ββββ | 24/63 [00:40<00:53, 1.38s/it]
Training 1/1 epoch (loss 2.6176): 38%|ββββ | 24/63 [00:41<00:53, 1.38s/it]
Training 1/1 epoch (loss 2.6176): 40%|ββββ | 25/63 [00:41<00:46, 1.21s/it]
Training 1/1 epoch (loss 2.6452): 40%|ββββ | 25/63 [00:44<00:46, 1.21s/it]
Training 1/1 epoch (loss 2.6452): 41%|βββββ | 26/63 [00:44<00:57, 1.55s/it]
Training 1/1 epoch (loss 2.7014): 41%|βββββ | 26/63 [00:45<00:57, 1.55s/it]
Training 1/1 epoch (loss 2.7014): 43%|βββββ | 27/63 [00:45<00:59, 1.65s/it]
Training 1/1 epoch (loss 2.5117): 43%|βββββ | 27/63 [00:46<00:59, 1.65s/it]
Training 1/1 epoch (loss 2.5117): 44%|βββββ | 28/63 [00:46<00:45, 1.29s/it]
Training 1/1 epoch (loss 2.7003): 44%|βββββ | 28/63 [00:47<00:45, 1.29s/it]
Training 1/1 epoch (loss 2.7003): 46%|βββββ | 29/63 [00:47<00:44, 1.32s/it]
Training 1/1 epoch (loss 2.6245): 46%|βββββ | 29/63 [00:49<00:44, 1.32s/it]
Training 1/1 epoch (loss 2.6245): 48%|βββββ | 30/63 [00:49<00:44, 1.35s/it]
Training 1/1 epoch (loss 2.4019): 48%|βββββ | 30/63 [00:49<00:44, 1.35s/it]
Training 1/1 epoch (loss 2.4019): 49%|βββββ | 31/63 [00:49<00:38, 1.19s/it]
Training 1/1 epoch (loss 2.7434): 49%|βββββ | 31/63 [00:51<00:38, 1.19s/it]
Training 1/1 epoch (loss 2.7434): 51%|βββββ | 32/63 [00:51<00:44, 1.42s/it]
Training 1/1 epoch (loss 2.5105): 51%|βββββ | 32/63 [00:53<00:44, 1.42s/it]
Training 1/1 epoch (loss 2.5105): 52%|ββββββ | 33/63 [00:53<00:41, 1.38s/it]
Training 1/1 epoch (loss 2.5027): 52%|ββββββ | 33/63 [00:53<00:41, 1.38s/it]
Training 1/1 epoch (loss 2.5027): 54%|ββββββ | 34/63 [00:53<00:32, 1.11s/it]
Training 1/1 epoch (loss 2.6453): 54%|ββββββ | 34/63 [00:55<00:32, 1.11s/it]
Training 1/1 epoch (loss 2.6453): 56%|ββββββ | 35/63 [00:55<00:37, 1.34s/it]
Training 1/1 epoch (loss 2.3857): 56%|ββββββ | 35/63 [00:57<00:37, 1.34s/it]
Training 1/1 epoch (loss 2.3857): 57%|ββββββ | 36/63 [00:57<00:39, 1.48s/it]
Training 1/1 epoch (loss 2.7490): 57%|ββββββ | 36/63 [00:58<00:39, 1.48s/it]
Training 1/1 epoch (loss 2.7490): 59%|ββββββ | 37/63 [00:58<00:32, 1.25s/it]
Training 1/1 epoch (loss 2.8562): 59%|ββββββ | 37/63 [00:59<00:32, 1.25s/it]
Training 1/1 epoch (loss 2.8562): 60%|ββββββ | 38/63 [00:59<00:31, 1.25s/it]
Training 1/1 epoch (loss 2.3489): 60%|ββββββ | 38/63 [01:01<00:31, 1.25s/it]
Training 1/1 epoch (loss 2.3489): 62%|βββββββ | 39/63 [01:01<00:35, 1.47s/it]
Training 1/1 epoch (loss 2.5452): 62%|βββββββ | 39/63 [01:02<00:35, 1.47s/it]
Training 1/1 epoch (loss 2.5452): 63%|βββββββ | 40/63 [01:02<00:28, 1.24s/it]
Training 1/1 epoch (loss 2.6134): 63%|βββββββ | 40/63 [01:03<00:28, 1.24s/it]
Training 1/1 epoch (loss 2.6134): 65%|βββββββ | 41/63 [01:03<00:31, 1.42s/it]
Training 1/1 epoch (loss 2.6486): 65%|βββββββ | 41/63 [01:04<00:31, 1.42s/it]
Training 1/1 epoch (loss 2.6486): 67%|βββββββ | 42/63 [01:04<00:27, 1.31s/it]
Training 1/1 epoch (loss 2.8719): 67%|βββββββ | 42/63 [01:06<00:27, 1.31s/it]
Training 1/1 epoch (loss 2.8719): 68%|βββββββ | 43/63 [01:06<00:27, 1.35s/it]
Training 1/1 epoch (loss 2.6747): 68%|βββββββ | 43/63 [01:08<00:27, 1.35s/it]
Training 1/1 epoch (loss 2.6747): 70%|βββββββ | 44/63 [01:08<00:28, 1.52s/it]
Training 1/1 epoch (loss 2.5425): 70%|βββββββ | 44/63 [01:09<00:28, 1.52s/it]
Training 1/1 epoch (loss 2.5425): 71%|ββββββββ | 45/63 [01:09<00:24, 1.38s/it]
Training 1/1 epoch (loss 2.4332): 71%|ββββββββ | 45/63 [01:10<00:24, 1.38s/it]
Training 1/1 epoch (loss 2.4332): 73%|ββββββββ | 46/63 [01:10<00:22, 1.32s/it]
Training 1/1 epoch (loss 2.5014): 73%|ββββββββ | 46/63 [01:12<00:22, 1.32s/it]
Training 1/1 epoch (loss 2.5014): 75%|ββββββββ | 47/63 [01:12<00:25, 1.62s/it]
Training 1/1 epoch (loss 2.4367): 75%|ββββββββ | 47/63 [01:14<00:25, 1.62s/it]
Training 1/1 epoch (loss 2.4367): 76%|ββββββββ | 48/63 [01:14<00:26, 1.74s/it]
Training 1/1 epoch (loss 2.5181): 76%|ββββββββ | 48/63 [01:15<00:26, 1.74s/it]
Training 1/1 epoch (loss 2.5181): 78%|ββββββββ | 49/63 [01:15<00:21, 1.53s/it]
Training 1/1 epoch (loss 2.6978): 78%|ββββββββ | 49/63 [01:17<00:21, 1.53s/it]
Training 1/1 epoch (loss 2.6978): 79%|ββββββββ | 50/63 [01:17<00:19, 1.53s/it]
Training 1/1 epoch (loss 2.6084): 79%|ββββββββ | 50/63 [01:18<00:19, 1.53s/it]
Training 1/1 epoch (loss 2.6084): 81%|ββββββββ | 51/63 [01:18<00:17, 1.43s/it]
Training 1/1 epoch (loss 2.5910): 81%|ββββββββ | 51/63 [01:19<00:17, 1.43s/it]
Training 1/1 epoch (loss 2.5910): 83%|βββββββββ | 52/63 [01:19<00:15, 1.38s/it]
Training 1/1 epoch (loss 2.6773): 83%|βββββββββ | 52/63 [01:21<00:15, 1.38s/it]
Training 1/1 epoch (loss 2.6773): 84%|βββββββββ | 53/63 [01:21<00:15, 1.52s/it]
Training 1/1 epoch (loss 2.5368): 84%|βββββββββ | 53/63 [01:22<00:15, 1.52s/it]
Training 1/1 epoch (loss 2.5368): 86%|βββββββββ | 54/63 [01:22<00:11, 1.22s/it]
Training 1/1 epoch (loss 2.7326): 86%|βββββββββ | 54/63 [01:24<00:11, 1.22s/it]
Training 1/1 epoch (loss 2.7326): 87%|βββββββββ | 55/63 [01:24<00:11, 1.41s/it]
Training 1/1 epoch (loss 2.6313): 87%|βββββββββ | 55/63 [01:26<00:11, 1.41s/it]
Training 1/1 epoch (loss 2.6313): 89%|βββββββββ | 56/63 [01:26<00:11, 1.58s/it]
Training 1/1 epoch (loss 2.6207): 89%|βββββββββ | 56/63 [01:26<00:11, 1.58s/it]
Training 1/1 epoch (loss 2.6207): 90%|βββββββββ | 57/63 [01:26<00:07, 1.24s/it]
Training 1/1 epoch (loss 2.5033): 90%|βββββββββ | 57/63 [01:28<00:07, 1.24s/it]
Training 1/1 epoch (loss 2.5033): 92%|ββββββββββ| 58/63 [01:28<00:06, 1.32s/it]
Training 1/1 epoch (loss 2.5215): 92%|ββββββββββ| 58/63 [01:29<00:06, 1.32s/it]
Training 1/1 epoch (loss 2.5215): 94%|ββββββββββ| 59/63 [01:29<00:05, 1.33s/it]
Training 1/1 epoch (loss 2.6683): 94%|ββββββββββ| 59/63 [01:29<00:05, 1.33s/it]
Training 1/1 epoch (loss 2.6683): 95%|ββββββββββ| 60/63 [01:29<00:03, 1.07s/it]
Training 1/1 epoch (loss 2.5546): 95%|ββββββββββ| 60/63 [01:32<00:03, 1.07s/it]
Training 1/1 epoch (loss 2.5546): 97%|ββββββββββ| 61/63 [01:32<00:03, 1.50s/it]
Training 1/1 epoch (loss 2.7586): 97%|ββββββββββ| 61/63 [01:34<00:03, 1.50s/it]
Training 1/1 epoch (loss 2.7586): 98%|ββββββββββ| 62/63 [01:34<00:01, 1.58s/it]
Training 1/1 epoch (loss 2.5320): 98%|ββββββββββ| 62/63 [01:34<00:01, 1.58s/it]
Training 1/1 epoch (loss 2.5320): 100%|ββββββββββ| 63/63 [01:34<00:00, 1.27s/it]
Training 1/1 epoch (loss 2.5320): 100%|ββββββββββ| 63/63 [01:34<00:00, 1.50s/it] |
| tokenizer config file saved in /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000-Q2-500/tokenizer_config.json |
| Special tokens file saved in /aifs4su/hansirui_1st/jiayi/setting3-imdb/tinyllama-3T/tinyllama-3T-s3-Q1-2000-Q2-500/special_tokens_map.json |
| wandb: ERROR Problem finishing run |
| Exception ignored in atexit callback: <bound method rank_zero_only.<locals>.wrapper of <safe_rlhf.logger.Logger object at 0x15512c356f90>> |
| Traceback (most recent call last): |
| File "/home/hansirui_1st/jiayi/resist/setting3/safe_rlhf/utils.py", line 212, in wrapper |
| return func(*args, **kwargs) |
| ^^^^^^^^^^^^^^^^^^^^^ |
| File "/home/hansirui_1st/jiayi/resist/setting3/safe_rlhf/logger.py", line 183, in close |
| self.wandb.finish() |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 406, in wrapper |
| return func(self, *args, **kwargs) |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 503, in wrapper |
| return func(self, *args, **kwargs) |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 451, in wrapper |
| return func(self, *args, **kwargs) |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 2309, in finish |
| return self._finish(exit_code) |
| ^^^^^^^^^^^^^^^^^^^^^^^ |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 406, in wrapper |
| return func(self, *args, **kwargs) |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 2337, in _finish |
| self._atexit_cleanup(exit_code=exit_code) |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 2550, in _atexit_cleanup |
| self._on_finish() |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/wandb_run.py", line 2806, in _on_finish |
| wait_with_progress( |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/mailbox/wait_with_progress.py", line 24, in wait_with_progress |
| return wait_all_with_progress( |
| ^^^^^^^^^^^^^^^^^^^^^^^ |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/mailbox/wait_with_progress.py", line 87, in wait_all_with_progress |
| return asyncio_compat.run(progress_loop_with_timeout) |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/site-packages/wandb/sdk/lib/asyncio_compat.py", line 27, in run |
| future = executor.submit(runner.run, fn) |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| File "/aifs4su/hansirui_1st/miniconda3/envs/jy-resist/lib/python3.11/concurrent/futures/thread.py", line 169, in submit |
| raise RuntimeError( |
| RuntimeError: cannot schedule new futures after interpreter shutdown |
|
|