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Update README Optimization Flags (#2691) #2941

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4 changes: 3 additions & 1 deletion README.md
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Expand Up @@ -145,7 +145,7 @@ torchtune exposes a number of levers for memory efficiency and performance. The
| Baseline | 25.5 | - | 2091 | - |
| [+ Packed Dataset](https://pytorch.org/torchtune/main/basics/packing.html) | 60.0 | +135.16% | 7075 | +238.40% |
| [+ Compile](https://pytorch.org/tutorials/intermediate/torch_compile_tutorial.html) | 51.0 | -14.93% | 8998 | +27.18% |
| [+ Chunked Cross Entropy](https://pytorch.org/torchtune/main/generated/torchtune.modules.loss.CEWithChunkedOutputLoss.html) | 42.9 | -15.83% | 9174 | +1.96% |
| [+ Linear Cross Entropy](https://pytorch.org/torchtune/main/generated/torchtune.modules.loss.CEWithChunkedOutputLoss.html) | 42.9 | -15.83% | 9174 | +1.96% |
| [+ Activation Checkpointing](https://pytorch.org/torchtune/main/tutorials/memory_optimizations.html#activation-checkpointing) | 24.9 | -41.93% | 7210 | -21.41% |
| [+ Fuse optimizer step into backward](https://pytorch.org/torchtune/main/tutorials/memory_optimizations.html#fusing-optimizer-step-into-backward-pass) | 23.1 | -7.29% | 7309 | +1.38% |
| [+ Activation Offloading](https://pytorch.org/torchtune/main/tutorials/memory_optimizations.html#activation-offloading) | 21.8 | -5.48% | 7301 | -0.11% |
Expand All @@ -154,6 +154,8 @@ torchtune exposes a number of levers for memory efficiency and performance. The
| [QLoRA](https://pytorch.org/torchtune/main/tutorials/memory_optimizations.html#quantized-low-rank-adaptation-qlora) | 4.6 | -45.71% | 8035 | -2.13% |

The final row in the table vs baseline + Packed Dataset uses **81.9%** less memory with a **284.3%** increase in tokens per second.
> ⚠️ Note: The command used to generate these results and the table values may need verification with the updated optimization setup. Please refer to Issue #2691 for context.


<details>
<summary>Command to reproduce final row.</summary>
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