Finetune GPT-2 on SST-2
shuangyichen opened this issue · comments
I want to finetune GPT-2 on SST-2. But I got an error
2023-12-18 21:57:27,452 (server:881) INFO: ----------- Starting training (Round #0) -------------
Traceback (most recent call last):
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/main.py", line 67, in
_ = runner.run()
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/fed_runner.py", line 401, in run
self._run_simulation()
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/fed_runner.py", line 484, in _run_simulation
self._handle_msg(msg)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/fed_runner.py", line 425, in _handle_msg
self.client[each_receiver].msg_handlersmsg.msg_type
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/workers/client.py", line 348, in callback_funcs_for_model_para
sample_size, model_para_all, results = self.trainer.train()
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/auxiliaries/decorators.py", line 7, in wrapper
num_samples_train, model_para, result_metric = func(
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/trainer.py", line 238, in train
num_samples = self._run_routine(MODE.TRAIN, hooks_set,
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/context.py", line 345, in wrapper
res = func(self, mode, hooks_set, dataset_name)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/trainer.py", line 274, in _run_routine
self._run_epoch(hooks_set)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/context.py", line 364, in wrapper
res = func(self, *args, **kwargs)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/trainer.py", line 291, in _run_epoch
self._run_batch(hooks_set)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/context.py", line 364, in wrapper
res = func(self, *args, **kwargs)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/trainer.py", line 307, in _run_batch
hook(self.ctx)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/llm/trainer/trainer.py", line 91, in _hook_on_batch_forward
input_ids = ctx.data_batch['input_ids'].to(ctx.device)
TypeError: list indices must be integers or slices, not str
Can you give me some suggestions? Thanks!
It looks like your data format does not match the requirement (json line with instruction, input, output, category), please see
It looks like your data format does not match the requirement (json line with
instruction,input,output,category), please seefor details.
Thanks for replying. I fix this one. But I got another error. It seems ctx.data_batch does not have 'labels'. But it does have 'input_ids' and 'attention_mask'.
Traceback (most recent call last):
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/main.py", line 67, in
_ = runner.run()
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/fed_runner.py", line 401, in run
self._run_simulation()
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/fed_runner.py", line 484, in _run_simulation
self._handle_msg(msg)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/fed_runner.py", line 425, in _handle_msg
self.client[each_receiver].msg_handlersmsg.msg_type
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/workers/client.py", line 348, in callback_funcs_for_model_para
sample_size, model_para_all, results = self.trainer.train()
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/auxiliaries/decorators.py", line 7, in wrapper
num_samples_train, model_para, result_metric = func(
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/trainer.py", line 238, in train
num_samples = self._run_routine(MODE.TRAIN, hooks_set,
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/context.py", line 345, in wrapper
res = func(self, mode, hooks_set, dataset_name)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/trainer.py", line 274, in _run_routine
self._run_epoch(hooks_set)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/context.py", line 364, in wrapper
res = func(self, *args, **kwargs)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/trainer.py", line 291, in _run_epoch
self._run_batch(hooks_set)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/context.py", line 364, in wrapper
res = func(self, *args, **kwargs)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/core/trainers/trainer.py", line 307, in _run_batch
hook(self.ctx)
File "/nfs/horai.dgpsrv/ondemand28/schen/csy/LoRA/new/FS-LLM/federatedscope/llm/trainer/trainer.py", line 95, in _hook_on_batch_forward
labels = ctx.data_batch['labels'].to(ctx.device)
KeyError: 'labels'
The labels are generated via output, you can set the output to true or false.
The labels are generated via
output, you can set theoutputtotrueorfalse.
All resolved. Thanks!