Comments (1)
Until the v1.1.1 release, this can be circumvented by disabling model selection (or copying the fixed implementation from the main branch).
from small-text.
Related Issues (20)
- Query by committee-of-committees HOT 1
- Throwing away stale data HOT 1
- Using active learning on already trained model HOT 3
- Provide an example of how to construct datasets without labels HOT 1
- Separate query functions from query strategy classes
- Provide animated GIF showing an active learning experiment HOT 2
- Add query strategy: QueryByCommittee
- Dataset cloning wraps the label
- Question: Regarding potential bottleneck during training of Classifiers HOT 18
- Class weighting causes nan values in loss
- TransformerBasedClassification: validations_per_epoch > 2 leaves the model in eval mode
- LightweightCoreset should allow for other distance metrics
- Add auto mixed precision flag to Pytorch-based Classifiers
- Make more SetFitClassification parameters configurable
- Cloning a nested DatasetsViews raises an AttributeError
- Inconsistency: TransformerBaseClassification.embed() returns np.float32 while SetFitClassification returns np.float64
- Add ActivePETs query strategy HOT 1
- Batch size in greedy coreset batching is different than expected
- Device-side assertion not passed when training on cuda device and when there are added tokens to the tokenizer HOT 2
- When using EmbeddingBasedQueryStrategy with some transformers, model has an unsupported input `token_type_ids` when creating embeddings. HOT 1
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from small-text.