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[ CI ] LM Eval Testing Expansion #326
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19f06cf
configs for expanded lm-eval testing
robertgshaw2-redhat 02d9647
updated configs
robertgshaw2-redhat b848d3c
added many configs
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stash
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updated
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nit on large models
robertgshaw2-redhat f7e1aca
cleanup configs
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rmove changes to utils.py
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lint
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cleanup utils.py
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update actions
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re added
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fix typo in action
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nit
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nit
robertgshaw2-redhat 441d718
removed utils.py changes
robertgshaw2-redhat e537aef
fix workflow
robertgshaw2-redhat fcfbd5e
config
robertgshaw2-redhat 999e056
fix workflow hopefully
robertgshaw2-redhat 1fa67e3
fixed lm-eval-workflow
robertgshaw2-redhat e788687
one more time...
robertgshaw2-redhat c7471de
added vllm baselining script
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last multi typo
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pass the correct config file
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Merge branch 'main' into expand-lm-eval-testing
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Update nm-run-lm-eval-vllm.sh
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Merge branch 'main' into expand-lm-eval-testing
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convert lm-eval test script to avoid for loop
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clean up lm-eval labels
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removed phi from small models, it is 28GB
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format
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Meta-Llama-3-70B-Instruct-FP8.yaml | ||
Meta-Llama-3-70B-Instruct.yaml | ||
Mixtral-8x22B-Instruct-v0.1-FP8.yaml | ||
Mixtral-8x22B-Instruct-v0.1.yaml | ||
Mixtral-8x7B-Instruct-v0.1-FP8.yaml | ||
Mixtral-8x7B-Instruct-v0.1.yaml | ||
Qwen2-57B-A14B-Instruct.yaml | ||
Qwen2-72B-Instruct.yaml | ||
Phi-3-medium-4k-instruct.yaml |
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gemma-7b-it.yaml | ||
Meta-Llama-3-8B-Instruct-FP8-KV.yaml | ||
Meta-Llama-3-8B-Instruct-FP8.yaml | ||
Meta-Llama-3-8B-Instruct-W4A16.yaml | ||
Meta-Llama-3-8B-Instruct.yaml | ||
Mistral-7B-Instruct-v0.3.yaml | ||
Qwen2-7B-Instruct.yaml |
11 changes: 11 additions & 0 deletions
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.github/lm-eval-configs/models/Meta-Llama-3-70B-Instruct-FP8.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m meta-llama/Meta-Llama-3-70B-Instruct -b 32 -l 250 -f 5 | ||
model_name: "meta-llama/Meta-Llama-3-70B-Instruct" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.900 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.900 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Meta-Llama-3-70B-Instruct.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m meta-llama/Meta-Llama-3-70B-Instruct -b 32 -l 250 -f 5 | ||
model_name: "meta-llama/Meta-Llama-3-70B-Instruct" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.888 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.888 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Meta-Llama-3-8B-Instruct-FP8-KV.yaml
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# ./nm-run-lm-eval-gsm-vllm-baseline.sh -m neuralmagic/Meta-Llama-3-8B-Instruct-FP8-KV -b 32 -l 250 -f 5 -t 1 | ||
model_name: "neuralmagic/Meta-Llama-3-8B-Instruct-FP8-KV" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.764 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.764 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Meta-Llama-3-8B-Instruct-FP8.yaml
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# ./nm-run-lm-eval-gsm-vllm-baseline.sh -m neuralmagic/Meta-Llama-3-8B-Instruct-FP8 -b 32 -l 250 -f 5 -t 1 | ||
model_name: "neuralmagic/Meta-Llama-3-8B-Instruct-FP8" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.744 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.740 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Meta-Llama-3-8B-Instruct-W4A16.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m TechxGenus/Meta-Llama-3-8B-Instruct-GPTQ -b 32 -l 250 -f 5 | ||
model_name: "TechxGenus/Meta-Llama-3-8B-Instruct-GPTQ" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.684 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.688 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Meta-Llama-3-8B-Instruct.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m meta-llama/Meta-Llama-3-8B-Instruct -b 32 -l 250 -f 5 | ||
model_name: "meta-llama/Meta-Llama-3-8B-Instruct" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.74 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.74 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Mistral-7B-Instruct-v0.3.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m mistralai/Mistral-7B-Instruct-v0.3 -b 32 -l 250 -f 5 | ||
model_name: "mistralai/Mistral-7B-Instruct-v0.3" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.524 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.524 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Mixtral-8x22B-Instruct-v0.1-FP8.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m mistralai/Mixtral-8x22B-Instruct-v0.1 -b 32 -l 250 -f 5 | ||
model_name: "mistralai/Mixtral-8x22B-Instruct-v0.1" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.840 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.844 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Mixtral-8x22B-Instruct-v0.1.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m mistralai/Mixtral-8x22B-Instruct-v0.1 -b 32 -l 250 -f 5 | ||
model_name: "mistralai/Mixtral-8x22B-Instruct-v0.1" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.876 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.880 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Mixtral-8x7B-Instruct-v0.1-FP8.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m mistralai/Mixtral-8x7B-Instruct-v0.1 -b 32 -l 250 -f 5 | ||
model_name: "mistralai/Mixtral-8x7B-Instruct-v0.1" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.616 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.620 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Mixtral-8x7B-Instruct-v0.1.yaml
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# bash ./nm-run-lm-eval-gsm-vllm-baseline.sh -m neuralmagic/Mixtral-8x7B-Instruct-v0.1-FP8 -b 32 -l 250 -f 5 -t 4 | ||
model_name: "mistralai/Mixtral-8x7B-Instruct-v0.1" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.616 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.628 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Phi-3-medium-4k-instruct.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m microsoft/Phi-3-medium-4k-instruct -b 16 -l 250 -f 5 | ||
model_name: "microsoft/Phi-3-medium-4k-instruct" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.840 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.852 | ||
limit: 250 | ||
num_fewshot: 5 |
11 changes: 11 additions & 0 deletions
11
.github/lm-eval-configs/models/Qwen2-57B-A14B-Instruct.yaml
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m Qwen/Qwen2-57B-A14B-Instruct -b 32 -l 250 -f 5 | ||
model_name: "Qwen/Qwen2-57B-A14B-Instruct" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.736 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.800 | ||
limit: 250 | ||
num_fewshot: 5 |
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m Qwen/Qwen2-72B-Instruct -b 16 -l 250 -f 5 | ||
model_name: "Qwen/Qwen2-72B-Instruct" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.828 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.856 | ||
limit: 250 | ||
num_fewshot: 5 |
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m Qwen/Qwen2-7B-Instruct -b 32 -l 250 -f 5 | ||
model_name: "Qwen/Qwen2-7B-Instruct" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.680 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.756 | ||
limit: 250 | ||
num_fewshot: 5 |
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# ./nm-run-lm-eval-gsm-hf-baseline.sh -m google/gemma-7b-it -b 16 -l 250 -f 5 | ||
model_name: "google/gemma-7b-it" | ||
tasks: | ||
- name: "gsm8k" | ||
metrics: | ||
- name: "exact_match,strict-match" | ||
value: 0.284 | ||
- name: "exact_match,flexible-extract" | ||
value: 0.324 | ||
limit: 250 | ||
num_fewshot: 5 |
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@@ -0,0 +1,2 @@ | ||
Meta-Llama-3-70B-Instruct.yaml | ||
Mixtral-8x7B-Instruct-v0.1.yaml |
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@@ -0,0 +1 @@ | ||
Meta-Llama-3-8B-Instruct.yaml |
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|
@@ -14,23 +14,19 @@ usage() { | |
echo | ||
echo " -m - huggingface stub or local directory of the model" | ||
echo " -b - batch size to run the evaluation at" | ||
echo " -d - device to use (e.g. cuda, cuda:0, auto, cpu)" | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. turns out this doesn't work, need to pass There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. nice find |
||
echo " -l - limit number of samples to run" | ||
echo " -f - number of fewshot samples to use" | ||
echo | ||
} | ||
|
||
while getopts "m:b:d:l:f:" OPT; do | ||
while getopts "m:b:l:f:" OPT; do | ||
case ${OPT} in | ||
m ) | ||
MODEL="$OPTARG" | ||
;; | ||
b ) | ||
BATCH_SIZE="$OPTARG" | ||
;; | ||
d ) | ||
DEVICE="$OPTARG" | ||
;; | ||
l ) | ||
LIMIT="$OPTARG" | ||
;; | ||
|
@@ -45,6 +41,6 @@ while getopts "m:b:d:l:f:" OPT; do | |
done | ||
|
||
lm_eval --model hf \ | ||
--model_args pretrained=$MODEL \ | ||
--model_args pretrained=$MODEL,parallelize=True \ | ||
--tasks gsm8k --num_fewshot $FEWSHOT --limit $LIMIT \ | ||
--batch_size $BATCH_SIZE --device $DEVICE | ||
--batch_size $BATCH_SIZE |
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@@ -0,0 +1,51 @@ | ||
#!/bin/bash | ||
# We can use this script to compute baseline accuracy on GSM for vllm. | ||
# We use this for fp8, which HF does not support. | ||
# | ||
# Make sure you have lm-eval-harness installed: | ||
# pip install git+https://github.com/EleutherAI/lm-evaluation-harness.git@9516087b81a61d0e220b22cc1b75be76de23bc10 | ||
|
||
usage() { | ||
echo`` | ||
echo "Runs lm eval harness on GSM8k using huggingface transformers." | ||
echo "This pathway is intended to be used to create baselines for " | ||
echo "our automated nm-test-accuracy workflow" | ||
echo | ||
echo "usage: ${0} <options>" | ||
echo | ||
echo " -m - huggingface stub or local directory of the model" | ||
echo " -b - batch size to run the evaluation at" | ||
echo " -l - limit number of samples to run" | ||
echo " -f - number of fewshot samples to use" | ||
echo " -t - tensor parallel size to run at" | ||
echo | ||
} | ||
|
||
while getopts "m:b:l:f:t:" OPT; do | ||
case ${OPT} in | ||
m ) | ||
MODEL="$OPTARG" | ||
;; | ||
b ) | ||
BATCH_SIZE="$OPTARG" | ||
;; | ||
l ) | ||
LIMIT="$OPTARG" | ||
;; | ||
f ) | ||
FEWSHOT="$OPTARG" | ||
;; | ||
t ) | ||
TP_SIZE="$OPTARG" | ||
;; | ||
\? ) | ||
usage | ||
exit 1 | ||
;; | ||
esac | ||
done | ||
|
||
lm_eval --model vllm \ | ||
--model_args pretrained=$MODEL,tensor_parallel_size=$TP_SIZE \ | ||
--tasks gsm8k --num_fewshot $FEWSHOT --limit $LIMIT \ | ||
--batch_size $BATCH_SIZE |
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Not sure where to put this, but it might be good to have a brief README in this repo with: a sketch of hardware requirements for these models and brief description of the various items in the "yaml". As an example for the latter, what does
num_fewshot
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Ill add this in the follow up