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Fine-tuning on a Sequence Classification Task #18

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leannmlindsey opened this issue Mar 9, 2024 · 1 comment
Closed

Fine-tuning on a Sequence Classification Task #18

leannmlindsey opened this issue Mar 9, 2024 · 1 comment

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@leannmlindsey
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I am trying to fine tune the new pre-trained model EVO, which uses the stripedhyena architecture on a sequence classification task. When trying to use AutoModelForSequenceClassification from hugging face I get this error (see ERROR MESSAGE #1). I then tried to set up a simple torch.nn layer for fine-tuning but I get a message that the forward() layer does not expect the "label" keyword in the dataset. (see ERROR MESSAGE #2).

Any advice would be appreciated. We are very excited to use this new model on our tasks. Thank you

ERROR MESSAGE #1
Traceback (most recent call last):
File "/home/llindsey1/CHPC/evo_finetune.py", line 32, in
seq_classification_model = AutoModelForSequenceClassification.from_config(config)
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/transformers/models/auto/auto_factory.py", line 437, in from_config
raise ValueError(
ValueError: Unrecognized configuration class <class 'transformers_modules.togethercomputer.evo-1-131k-base.8eb9480ea22de5f86eeebc1199a76b63b42d7170.configuration_hyena.StripedHyenaConfig'> for this kind of AutoModel: AutoModelForSequenceClassification.
Model type should be one of AlbertConfig, BartConfig, BertConfig, BigBirdConfig, BigBirdPegasusConfig, BioGptConfig, BloomConfig, CamembertConfig, CanineConfig, LlamaConfig, ConvBertConfig, CTRLConfig, Data2VecTextConfig, DebertaConfig, DebertaV2Config, DistilBertConfig, ElectraConfig, ErnieConfig, ErnieMConfig, EsmConfig, FalconConfig, FlaubertConfig, FNetConfig, FunnelConfig, GemmaConfig, GPT2Config, GPT2Config, GPTBigCodeConfig, GPTNeoConfig, GPTNeoXConfig, GPTJConfig, IBertConfig, LayoutLMConfig, LayoutLMv2Config, LayoutLMv3Config, LEDConfig, LiltConfig, LlamaConfig, LongformerConfig, LukeConfig, MarkupLMConfig, MBartConfig, MegaConfig, MegatronBertConfig, MistralConfig, MixtralConfig, MobileBertConfig, MPNetConfig, MptConfig, MraConfig, MT5Config, MvpConfig, NezhaConfig, NystromformerConfig, OpenLlamaConfig, OpenAIGPTConfig, OPTConfig, PerceiverConfig, PersimmonConfig, PhiConfig, PLBartConfig, QDQBertConfig, Qwen2Config, ReformerConfig, RemBertConfig, RobertaConfig, RobertaPreLayerNormConfig, RoCBertConfig, RoFormerConfig, SqueezeBertConfig, StableLmConfig, T5Config, TapasConfig, TransfoXLConfig, UMT5Config, XLMConfig, XLMRobertaConfig, XLMRobertaXLConfig, XLNetConfig, XmodConfig, YosoConfig.

ERROR MESSAGE #2
File "/home/llindsey1/CHPC/evo_finetune_phage.py", line 96, in
trainer.train()
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/transformers/trainer.py", line 1624, in train
return inner_training_loop(
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/transformers/trainer.py", line 1961, in _inner_training_loop
tr_loss_step = self.training_step(model, inputs)
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/transformers/trainer.py", line 2902, in training_step
loss = self.compute_loss(model, inputs)
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/transformers/trainer.py", line 2925, in compute_loss
outputs = model(**inputs)
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
return forward_call(*args, **kwargs)
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/accelerate/utils/operations.py", line 817, in forward
return model_forward(*args, **kwargs)
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/accelerate/utils/operations.py", line 805, in call
return convert_to_fp32(self.model_forward(*args, **kwargs))
File "/home/llindsey1/.conda/envs/EVO/lib/python3.9/site-packages/torch/amp/autocast_mode.py", line 16, in decorate_autocast
return func(*args, **kwargs)
TypeError: forward() got an unexpected keyword argument 'label'
0%| | 0/100 [00:00<?, ?it/s]

@leannmlindsey
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Was able to solve this by changing the keyword to "labels" instead of "label"

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