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Make errors for loss-less models more user-friendly (#18233)

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Sylvain Gugger 2022-07-21 11:52:33 +02:00 committed by GitHub
parent 43a5375cc1
commit ba552dd027
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1 changed files with 14 additions and 1 deletions
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15
src/transformers/trainer.py
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@ -69,7 +69,7 @@ from .deepspeed import deepspeed_init, is_deepspeed_zero3_enabled
from .dependency_versions_check import dep_version_check
from .modelcard import TrainingSummary
from .modeling_utils import PreTrainedModel, load_sharded_checkpoint, unwrap_model
from .models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from .models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES, MODEL_MAPPING_NAMES
from .optimization import Adafactor, get_scheduler
from .pytorch_utils import ALL_LAYERNORM_LAYERS
from .tokenization_utils_base import PreTrainedTokenizerBase
@ -351,6 +351,14 @@ class Trainer:
)
self.model_init = model_init
if model.__class__.__name__ in MODEL_MAPPING_NAMES:
raise ValueError(
f"The model you have picked ({model.__class__.__name__}) cannot be used as is for training: it only "
"computes hidden states and does not accept any labels. You should choose a model with a head "
"suitable for your task like any of the `AutoModelForXxx` listed at "
"https://huggingface.co/docs/transformers/model_doc/auto."
)
if hasattr(model, "is_parallelizable") and model.is_parallelizable and model.model_parallel:
self.is_model_parallel = True
else:
@ -2503,6 +2511,11 @@ class Trainer:
else:
loss = self.label_smoother(outputs, labels)
else:
if isinstance(outputs, dict) and "loss" not in outputs:
raise ValueError(
"The model did not return a loss from the inputs, only the following keys: "
f"{','.join(outputs.keys())}. For reference, the inputs it received are {','.join(inputs.keys())}."
)
# We don't use .loss here since the model may return tuples instead of ModelOutput.
loss = outputs["loss"] if isinstance(outputs, dict) else outputs[0]