deepspeedai / deepspeedai/DeepSpeedExamples
Overflow in deepspeed-chat LoRA and BF16 mode
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Description
- Example: Deepspeed-chat
- Model: Llama2-7b-hf
- Mode: LoRA, lora_dim=128
- precision: FP16
- Output log as below:
- Question: Does the log mean it's training correctly? I found the log is different from the log of SFT and LoRA only mode, which can output loss in each step. If not correct, how to make LoRA mode run correcly?
Model Parameters: 6.927 B, Latency: 6.08s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.06s, TFLOPs: 1.73, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.07s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.07s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.07s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.07s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.07s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.07s, TFLOPs: 1.73, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
[2023-10-20 09:49:17,004] [INFO] [logging.py:96:log_dist] [Rank 0] step=40, skipped=6, lr=[9.618683345445294e-06, 0.0004983773754116733], mom=[(0.9, 0.95), (0.9, 0.95)]
[2023-10-20 09:49:17,004] [INFO] [timer.py:260:stop] epoch=0/micro_step=40/global_step=40, RunningAvgSamplesPerSec=5.187625237365746, CurrSamplesPerSec=5.008550092748559, MemAllocated=3.9GB, MaxMemAllocated=6.71GB
Model Parameters: 6.927 B, Latency: 6.39s, TFLOPs: 1.64, Samples/sec: 0.63, Time/seq 1.60s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.06s, TFLOPs: 1.73, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.07s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.09s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.08s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Model Parameters: 6.927 B, Latency: 6.07s, TFLOPs: 1.72, Samples/sec: 0.66, Time/seq 1.52s, Batch Size: 4, Sequence Length: 512
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the Deepspeed-chat example and compare its LoRA and BF16/FP16 execution with the SFT and LoRA-only modes mentioned in the report. Determine whether the repeated performance logs indicate correct training and whether loss output is expected; done means the behavior is explained or the underlying logging or training issue is resolved.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100