Upload llm_metaeval_eval_harness_mmlu.ipynb
Browse files- llm_metaeval_eval_harness_mmlu.ipynb +1373 -79
llm_metaeval_eval_harness_mmlu.ipynb
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@@ -13,9 +13,189 @@
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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},
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"outputs": [
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"source": [
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"!pip install -r https://huggingface.co/flunardelli/llm-metaeval/raw/main/requirements.txt"
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]
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"fewshot_split: dev\n",
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"fewshot_config:\n",
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" sampler: first_n\n",
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"output_type: multiple_choice\n",
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"doc_to_text: \"{{question.strip()}}\\nA. {{choices[0]}}\\nB. {{choices[1]}}\\nC. {{choices[2]}}\\nD. {{choices[3]}}\\nAnswer:\"\n",
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"doc_to_choice: [\"A\", \"B\", \"C\", \"D\"]\n",
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" - metric: acc\n",
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" aggregation: mean\n",
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" higher_is_better: true\n",
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" - metric: acc_norm\n",
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" aggregation: mean\n",
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" higher_is_better: true\n",
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"\"\"\"\n",
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"create_task(YAML_mmlu_en_us_string, 'mmlu_en_us.yaml')\n",
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"os.environ['TASKS'] = 'mmlu_all'\n"
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"background_save": true
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},
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"id": "IzP5nyP0Gwk8"
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},
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"outputs": [],
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"source": [
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"!
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"--model hf --model_args pretrained=meta-llama/Llama-3.2-1B-Instruct,parallelize=True \\\n",
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"--tasks $TASKS \\\n",
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"--include_path $TASK_FOLDER/. --output $OUTPUT_FOLDER --
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"--batch_size
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"#--limit 10 \\"
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]
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},
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{
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"cell_type": "code",
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"
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"hf_upload_folder(BASE_FOLDER)"
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],
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"metadata": {
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"id": "uMoitxJkHerH"
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"background_save": true
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},
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"id": "oIACOAhDW5ow"
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},
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"outputs": [],
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"source": [
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"!
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"--model hf --model_args pretrained=meta-llama/Llama-3.2-3B-Instruct,parallelize=True \\\n",
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"--tasks $TASKS \\\n",
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"--include_path $TASK_FOLDER/. --output $OUTPUT_FOLDER --
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"--batch_size
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"#--limit 10 \\"
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]
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},
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{
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"cell_type": "code",
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"hf_upload_folder(BASE_FOLDER)"
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],
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"metadata": {
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"id": "eIUOqu5sHfkM"
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"background_save": true
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"id": "cFFYPzBIYGf7"
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},
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"outputs": [],
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"source": [
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"!
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"--model hf --model_args pretrained=meta-llama/Meta-Llama-3-8B,parallelize=True \\\n",
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"--tasks $TASKS \\\n",
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"--include_path $TASK_FOLDER/. --output $OUTPUT_FOLDER --
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"#--limit 10 \\"
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]
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},
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"cell_type": "code",
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"hf_upload_folder(BASE_FOLDER)"
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],
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"metadata": {
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"id": "xsL82Q4SHgMn"
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"cell_type": "markdown",
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"colab": {
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"outputs": [
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{
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"cell_type": "code",
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"source": [
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"hf_upload_folder(BASE_FOLDER)"
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],
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"metadata": {
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"id": "jE5r8gVDHhAz"
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},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "3cHI2qxN2fJ0"
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},
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"outputs": [],
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"source": [
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"!
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"--model hf --model_args pretrained=mistralai/Mixtral-
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"--tasks $TASKS \\\n",
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"--include_path $TASK_FOLDER/. --output $OUTPUT_FOLDER
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"#--limit 10 \\"
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]
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},
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "
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},
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"outputs": [
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"source": [
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"hf_upload_folder(BASE_FOLDER)"
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]
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},
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"language_info": {
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"name": "python"
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| 287 |
}
|
| 288 |
},
|
| 289 |
"nbformat": 4,
|
|
|
|
| 13 |
"cell_type": "code",
|
| 14 |
"execution_count": null,
|
| 15 |
"metadata": {
|
| 16 |
+
"colab": {
|
| 17 |
+
"base_uri": "https://localhost:8080/"
|
| 18 |
+
},
|
| 19 |
+
"id": "kGW7vfRkrqHe",
|
| 20 |
+
"outputId": "a51e7052-6e2d-431e-a46b-63d92254c8cc"
|
| 21 |
},
|
| 22 |
+
"outputs": [
|
| 23 |
+
{
|
| 24 |
+
"output_type": "stream",
|
| 25 |
+
"name": "stdout",
|
| 26 |
+
"text": [
|
| 27 |
+
"Collecting lm_eval@ git+https://github.com/EleutherAI/[email protected] (from -r https://huggingface.co/flunardelli/llm-metaeval/raw/main/requirements.txt (line 3))\n",
|
| 28 |
+
" Cloning https://github.com/EleutherAI/lm-evaluation-harness.git (to revision v0.4.6) to /tmp/pip-install-pwn3euso/lm-eval_15e9ff6cb88d46aa9b65c222332a3c3b\n",
|
| 29 |
+
" Running command git clone --filter=blob:none --quiet https://github.com/EleutherAI/lm-evaluation-harness.git /tmp/pip-install-pwn3euso/lm-eval_15e9ff6cb88d46aa9b65c222332a3c3b\n",
|
| 30 |
+
" Running command git checkout -q 9d36354e6422db94c374dc476c093b1495370983\n",
|
| 31 |
+
" Resolved https://github.com/EleutherAI/lm-evaluation-harness.git to commit 9d36354e6422db94c374dc476c093b1495370983\n",
|
| 32 |
+
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
|
| 33 |
+
" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
|
| 34 |
+
" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
|
| 35 |
+
"Requirement already satisfied: accelerate==1.1.1 in /usr/local/lib/python3.10/dist-packages (from -r https://huggingface.co/flunardelli/llm-metaeval/raw/main/requirements.txt (line 1)) (1.1.1)\n",
|
| 36 |
+
"Collecting bitsandbytes==0.44.1 (from -r https://huggingface.co/flunardelli/llm-metaeval/raw/main/requirements.txt (line 2))\n",
|
| 37 |
+
" Downloading bitsandbytes-0.44.1-py3-none-manylinux_2_24_x86_64.whl.metadata (3.5 kB)\n",
|
| 38 |
+
"Requirement already satisfied: huggingface-hub>=0.21.0 in /usr/local/lib/python3.10/dist-packages (from accelerate==1.1.1->-r https://huggingface.co/flunardelli/llm-metaeval/raw/main/requirements.txt (line 1)) (0.26.2)\n",
|
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"Installing collected packages: word2number, sqlitedict, zstandard, xxhash, tcolorpy, pybind11, portalocker, pathvalidate, mbstrdecoder, jsonlines, fsspec, dill, colorama, typepy, tqdm-multiprocess, sacrebleu, rouge-score, multiprocess, bitsandbytes, DataProperty, tabledata, datasets, pytablewriter, evaluate, lm_eval\n",
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"\u001b[0mSuccessfully installed DataProperty-1.0.1 bitsandbytes-0.44.1 colorama-0.4.6 datasets-3.1.0 dill-0.3.8 evaluate-0.4.3 fsspec-2024.9.0 jsonlines-4.0.0 lm_eval-0.4.5 mbstrdecoder-1.1.3 multiprocess-0.70.16 pathvalidate-3.2.1 portalocker-3.0.0 pybind11-2.13.6 pytablewriter-1.2.0 rouge-score-0.1.2 sacrebleu-2.4.3 sqlitedict-2.1.0 tabledata-1.3.3 tcolorpy-0.1.6 tqdm-multiprocess-0.0.11 typepy-1.3.2 word2number-1.1 xxhash-3.5.0 zstandard-0.23.0\n"
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]
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}
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],
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"source": [
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"!pip install -r https://huggingface.co/flunardelli/llm-metaeval/raw/main/requirements.txt"
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]
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"fewshot_split: dev\n",
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"fewshot_config:\n",
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" sampler: first_n\n",
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"num_fewshot: 5\n",
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"output_type: multiple_choice\n",
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"doc_to_text: \"{{question.strip()}}\\nA. {{choices[0]}}\\nB. {{choices[1]}}\\nC. {{choices[2]}}\\nD. {{choices[3]}}\\nAnswer:\"\n",
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"doc_to_choice: [\"A\", \"B\", \"C\", \"D\"]\n",
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" - metric: acc\n",
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" aggregation: mean\n",
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" higher_is_better: true\n",
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"\"\"\"\n",
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"create_task(YAML_mmlu_en_us_string, 'mmlu_en_us.yaml')\n",
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"os.environ['TASKS'] = 'mmlu_all'\n"
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "IzP5nyP0Gwk8"
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},
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"outputs": [],
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"source": [
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+
"!lm_eval \\\n",
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"--model hf --model_args pretrained=meta-llama/Llama-3.2-1B-Instruct,revision=d0a2081ed47e20ce524e8bc5d132f3fad2f69ff0,trust_remote_code=False,dtype=bfloat16,parallelize=True \\\n",
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"--tasks $TASKS \\\n",
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+
"--include_path $TASK_FOLDER/. --output $OUTPUT_FOLDER --log_samples \\\n",
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"--batch_size auto &> run.log\n",
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"#--limit 10 \\"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "uMoitxJkHerH",
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 77,
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"referenced_widgets": [
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"7b825d3c10be4fa6abd7c115f8e4e1f2",
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"d426e85f0ce641d381d52927df68c278",
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]
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"outputId": "b833672c-b855-494d-f480-8417ef199be8"
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},
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"outputs": [
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{
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"output_type": "display_data",
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"data": {
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},
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"metadata": {}
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],
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"source": [
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"hf_upload_folder(BASE_FOLDER)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "oIACOAhDW5ow"
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},
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"outputs": [],
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"source": [
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+
"!lm_eval \\\n",
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+
"--model hf --model_args pretrained=meta-llama/Llama-3.2-3B-Instruct,revision=392a143b624368100f77a3eafaa4a2468ba50a72,trust_remote_code=False,dtype=bfloat16,parallelize=True \\\n",
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"--tasks $TASKS \\\n",
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"--include_path $TASK_FOLDER/. --output $OUTPUT_FOLDER --log_samples \\\n",
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"--batch_size auto &> run.log\n",
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"#--limit 10 \\"
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]
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},
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{
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"execution_count": null,
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"metadata": {
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"id": "eIUOqu5sHfkM",
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 77,
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"referenced_widgets": [
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