Comments (1)
Fixed via #445....the SSR and max duration are not persisted in a checkpoint, so whatever values are passed to the trainer upon checkpoint resume will be used.
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Related Issues (20)
- Forward metric name to `update_metric` HOT 7
- AttributeError on DeviceMPS HOT 2
- Using streaming and composer HOT 1
- `DataSpec` can't be used with `StreamingDataset` when `world_size>1`
- CUDA error: initialization error during distributed training when num_workers > 0 in eval_dataloader and metrics are not None HOT 2
- WandBLogger throws an Exception in any mode except 'online' HOT 4
- is AMD + RoCM available? HOT 1
- state_dict_type: sharded does not saves all shards to s3 HOT 16
- HuggingFace Pre-trained model Fine Tuning Error HOT 2
- Stuck at train.fit() and print nothing HOT 3
- eval drops when i have multi_eval dataset HOT 5
- Access state.outputs: RuntimeError: CUDA error: an illegal memory access was encountered HOT 2
- Crash when training Llama 2 from HF on ROCm HOT 3
- InContextLearning*Dataset Default padding sides hardcoded? HOT 1
- WandBLogger init is a hot mess HOT 2
- Bump `torchmetrics` HOT 2
- Calling the `Trainer` without using the `composer` comand in `0.18` HOT 10
- `0.18.1` not available in PyPI HOT 3
- Saving checkpoints on network drive fails due to symlinks HOT 1
- Add support for Pytorch 2.2.0 HOT 1
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