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"id": "18d5599f-992d-4d8e-a90c-4d43774be473", "metadata": {}, "outputs": [ @@ -510,7 +454,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 19, "id": "baeee903-3dce-48b2-93c3-7a697d8c6daf", "metadata": {}, "outputs": [], @@ -539,9 +483,9 @@ "Collecting threadpoolctl>=2.0.0 (from scikit-learn)\n", " Downloading threadpoolctl-3.3.0-py3-none-any.whl.metadata (13 kB)\n", "Downloading scikit_learn-1.4.1.post1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.1 MB)\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.1/12.1 MB\u001b[0m \u001b[31m183.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m \u001b[36m0:00:01\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.1/12.1 MB\u001b[0m \u001b[31m307.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m \u001b[36m0:00:01\u001b[0m\n", "\u001b[?25hDownloading joblib-1.3.2-py3-none-any.whl (302 kB)\n", - "\u001b[2K 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@@ " lr_scheduler_type=\"cosine\",\n", " save_strategy=\"epoch\",\n", " logging_steps=50,\n", - " max_steps=20000,\n", + " max_steps=10000,\n", " num_train_epochs=3,\n", " push_to_hub=True\n", " )" @@ -684,7 +628,7 @@ "text": [ "Requirement already satisfied: jupyterlab in /usr/local/lib/python3.11/site-packages (4.1.0)\n", "Collecting jupyterlab\n", - " Downloading jupyterlab-4.1.1-py3-none-any.whl.metadata (15 kB)\n", + " Downloading jupyterlab-4.1.2-py3-none-any.whl.metadata (15 kB)\n", "Collecting jupyterlab-git\n", " Downloading jupyterlab_git-0.50.0-py3-none-any.whl.metadata (31 kB)\n", "Requirement already satisfied: async-lru>=1.0.0 in /usr/local/lib/python3.11/site-packages (from jupyterlab) (2.0.4)\n", @@ -727,12 +671,12 @@ "Requirement already satisfied: jsonschema>=4.18.0 in /usr/local/lib/python3.11/site-packages (from jupyterlab-server<3,>=2.19.0->jupyterlab) (4.21.1)\n", "Requirement already satisfied: requests>=2.31 in /usr/local/lib/python3.11/site-packages (from 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"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m234.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m342.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hDownloading lightning_utilities-0.10.1-py3-none-any.whl (24 kB)\n", "Downloading torchmetrics-1.3.1-py3-none-any.whl (840 kB)\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m840.4/840.4 kB\u001b[0m \u001b[31m545.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m840.4/840.4 kB\u001b[0m \u001b[31m591.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hInstalling collected packages: tokenizers, triton, nvidia-nccl-cu12, lightning-utilities, transformers, torch, torchmetrics, accelerate, pytorch-lightning\n", " Attempting uninstall: tokenizers\n", " Found existing installation: tokenizers 0.15.2\n", @@ -1011,7 +956,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 16, "id": "d76b4865-df75-4793-b8b9-d97523445945", "metadata": {}, "outputs": [], @@ -1033,8 +978,8 @@ "\n", "
50 | \n", - "1.029900 | \n", + "1.458400 | \n", "
100 | \n", - "1.099000 | \n", + "1.300500 | \n", "
150 | \n", - "1.001700 | \n", + "1.163600 | \n", "
200 | \n", - "1.084800 | \n", + "1.231700 | \n", "
250 | \n", - "1.074200 | \n", + "1.215000 | \n", "
300 | \n", - "1.026600 | \n", + "1.167400 | \n", "
350 | \n", - "0.933200 | \n", + "1.061700 | \n", "
400 | \n", - "1.056400 | \n", + "1.182300 | \n", "
450 | \n", - "0.972000 | \n", + "1.107400 | \n", "
500 | \n", - "1.025000 | \n", + "1.168000 | \n", "
550 | \n", - "0.973800 | \n", + "1.102500 | \n", "
600 | \n", - "0.996200 | \n", + "1.121800 | \n", "
650 | \n", - "1.035000 | \n", + "1.145500 | \n", "
700 | \n", - "1.044400 | \n", + "1.145000 | \n", "
750 | \n", - "1.041000 | \n", + "1.155200 | \n", "
800 | \n", - "1.005200 | \n", + "1.099600 | \n", "
850 | \n", - "0.991400 | \n", + "1.090800 | \n", "
900 | \n", - "0.989400 | \n", + "1.080600 | \n", "
950 | \n", - "1.038700 | \n", + "1.129900 | \n", "
1000 | \n", - "0.988900 | \n", + "1.061500 | \n", "
1050 | \n", - "1.018900 | \n", + "1.099200 | \n", "
1100 | \n", - "1.050900 | \n", + "1.122900 | \n", "
1150 | \n", - "1.060600 | \n", + "1.128500 | \n", "
1200 | \n", - "1.021900 | \n", + "1.085700 | \n", "
1250 | \n", - "1.115900 | \n", + "1.165000 | \n", "
1300 | \n", - "1.027500 | \n", + "1.083300 | \n", "
1350 | \n", - "1.036700 | \n", + "1.082900 | \n", "
1400 | \n", - "1.087600 | \n", + "1.131900 | \n", "
1450 | \n", - "1.030200 | \n", + "1.066800 | \n", "
1500 | \n", - "1.094000 | \n", + "1.128600 | \n", "
1550 | \n", - "1.124500 | \n", + "1.159600 | \n", "
1600 | \n", - "1.095000 | \n", + "1.120100 | \n", "
1650 | \n", - "1.014200 | \n", + "1.042100 | \n", "
1700 | \n", - "1.083000 | \n", + "1.105800 | \n", "
1750 | \n", - "1.104400 | \n", + "1.124700 | \n", "
1800 | \n", - "1.024800 | \n", + "1.043800 | \n", "
1850 | \n", - "1.103400 | \n", + "1.120900 | \n", "
1900 | \n", - "1.066900 | \n", + "1.081700 | \n", "
1950 | \n", - "1.109600 | \n", + "1.123200 | \n", "
2000 | \n", - "1.060600 | \n", + "1.074400 | \n", "
2050 | \n", - "1.153800 | \n", + "1.166000 | \n", "
2100 | \n", - "1.080800 | \n", + "1.097300 | \n", "
2150 | \n", - "0.972200 | \n", + "0.989200 | \n", "
2200 | \n", - "0.977700 | \n", + "0.988200 | \n", "
2250 | \n", - "1.067500 | \n", + "1.080400 | \n", "
2300 | \n", - "1.088700 | \n", + "1.100700 | \n", "
2350 | \n", - "1.060200 | \n", + "1.074600 | \n", "
2400 | \n", - "0.995500 | \n", + "1.009900 | \n", "
2450 | \n", - "1.104500 | \n", + "1.117800 | \n", "
2500 | \n", - "1.118800 | \n", + "1.131300 | \n", "
2550 | \n", - "1.023300 | \n", + "1.033500 | \n", "
2600 | \n", - "1.080900 | \n", + "1.094400 | \n", "
2650 | \n", - "1.059300 | \n", + "1.072600 | \n", "
2700 | \n", - "1.087700 | \n", + "1.099600 | \n", "
2750 | \n", - "0.982500 | \n", + "0.988700 | \n", "
2800 | \n", - "0.996400 | \n", + "1.009600 | \n", "
2850 | \n", - "1.033600 | \n", + "1.044400 | \n", "
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2950 | \n", - "0.974400 | \n", + "0.983500 | \n", "
3000 | \n", - "0.971100 | \n", + "0.982800 | \n", "
3050 | \n", - "1.096000 | \n", + "1.104500 | \n", "
3100 | \n", - "1.144400 | \n", + "1.155100 | \n", "
3150 | \n", - "1.018700 | \n", + "1.029100 | \n", "
3200 | \n", - "1.038900 | \n", + "1.047900 | \n", "
3250 | \n", - "1.036000 | \n", + "1.045000 | \n", "
3300 | \n", - "0.979400 | \n", + "0.987200 | \n", "
3350 | \n", - "0.959100 | \n", + "0.967300 | \n", "
3400 | \n", - "1.054500 | \n", + "1.063000 | \n", "
3450 | \n", - "0.999600 | \n", + "1.003900 | \n", "
3500 | \n", - "0.991500 | \n", + "0.997600 | \n", "
3550 | \n", - "1.058600 | \n", + "1.066800 | \n", "
3600 | \n", - "1.090700 | \n", + "1.099700 | \n", "
3650 | \n", - "1.040200 | \n", + "1.045500 | \n", "
3700 | \n", - "1.054600 | \n", + "1.060900 | \n", "
3750 | \n", - "1.079500 | \n", + "1.084000 | \n", "
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3850 | \n", - "1.069000 | \n", + "1.074100 | \n", "
3900 | \n", - "0.980800 | \n", + "0.991600 | \n", "
3950 | \n", - "1.068200 | \n", + "1.074900 | \n", "
4000 | \n", - "1.077300 | \n", + "1.082100 | \n", "
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4800 | \n", - "1.015000 | \n", - "|
4850 | \n", - "0.936600 | \n", - "|
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5300 | \n", - "0.996400 | \n", - "|
5350 | \n", - "0.913700 | \n", - "|
5400 | \n", - "1.001200 | \n", - "|
5450 | \n", - "0.984900 | \n", - "|
5500 | \n", - "1.006300 | \n", - "|
5550 | \n", - "0.965200 | \n", - "|
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6900 | \n", - "0.960900 | \n", - "|
6950 | \n", - "0.914900 | \n", - "|
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7050 | \n", - "0.880100 | \n", - "|
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7150 | \n", - "0.911300 | \n", - "|
7200 | \n", - "0.939300 | \n", - "|
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8000 | \n", - "0.885000 | \n", - "|
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9700 | \n", - "0.897800 | \n", - "|
9750 | \n", - "0.909800 | \n", - "|
9800 | \n", - "0.860100 | \n", - "|
9850 | \n", - "0.847400 | \n", - "|
9900 | \n", - "0.894800 | \n", - "|
9950 | \n", - "0.941600 | \n", - "|
10000 | \n", - "0.877000 | \n", - "|
10050 | \n", - "0.880500 | \n", - "|
10100 | \n", - "0.923500 | \n", - "|
10150 | \n", - "0.900100 | \n", - "|
10200 | \n", - "0.832500 | \n", - "|
10250 | \n", - "0.780100 | \n", - "|
10300 | \n", - "0.822500 | \n", - "|
10350 | \n", - "0.896400 | \n", - "|
10400 | \n", - "0.859800 | \n", - "|
10450 | \n", - "0.968900 | \n", - "|
10500 | \n", - "0.936400 | \n", - "|
10550 | \n", - "0.893900 | \n", - "|
10600 | \n", - "0.916400 | \n", - "|
10650 | \n", - "0.818800 | \n", - "|
10700 | \n", - "0.841100 | \n", - "|
10750 | \n", - "0.818100 | \n", - "|
10800 | \n", - "0.883900 | \n", - "|
10850 | \n", - "0.880400 | \n", - "|
10900 | \n", - "0.810100 | \n", - "|
10950 | \n", - "0.878800 | \n", - "|
11000 | \n", - "0.818500 | \n", - "|
11050 | \n", - "0.924100 | \n", - "|
11100 | \n", - "0.871100 | \n", - "|
11150 | \n", - "0.879600 | \n", - "|
11200 | \n", - "0.857600 | \n", - "|
11250 | \n", - "0.877800 | \n", - "|
11300 | \n", - "0.923600 | \n", - "|
11350 | \n", - "0.831800 | \n", - "|
11400 | \n", - "0.840900 | \n", - "|
11450 | \n", - "0.885600 | \n", - "|
11500 | \n", - "0.858100 | \n", - "|
11550 | \n", - "0.908300 | \n", - "|
11600 | \n", - "0.909800 | \n", - "|
11650 | \n", - "0.967500 | \n", - "|
11700 | \n", - "0.880500 | \n", - "|
11750 | \n", - "0.929400 | \n", - "|
11800 | \n", - "0.878400 | \n", - "|
11850 | \n", - "0.824400 | \n", - "|
11900 | \n", - "0.932200 | \n", - "|
11950 | \n", - "0.863500 | \n", - "|
12000 | \n", - "0.890200 | \n", - "|
12050 | \n", - "0.870400 | \n", - "|
12100 | \n", - "0.854300 | \n", - "|
12150 | \n", - "0.903400 | \n", - "|
12200 | \n", - "0.846000 | \n", - "|
12250 | \n", - "0.841000 | \n", + "1.051500 | \n", "
" @@ -2056,9 +1345,9 @@ "from transformers import AutoModelForCausalLM\n", "import torch\n", "model = AutoModelForCausalLM.from_pretrained(\"microsoft/phi-2\", trust_remote_code=True, torch_dtype=torch.float32)\n", - "peft_model = PeftModel.from_pretrained(model, \"aissatoubalde/lab\", from_transformers=True)\n", - "model = peft_model.merge_and_unload()\n", - "model" + "# peft_model = PeftModel.from_pretrained(model, \"aissatoubalde/lab\", from_transformers=True)\n", + "# model = peft_model.merge_and_unload()\n", + "# model" ] }, {