diff --git "a/U4-finetuning.ipynb" "b/U4-finetuning.ipynb"
new file mode 100644--- /dev/null
+++ "b/U4-finetuning.ipynb"
@@ -0,0 +1,8623 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "1Ni4QFjWo8cp",
+ "outputId": "072d5f25-c78d-4d43-9c6d-9e718b3953ef"
+ },
+ "outputs": [],
+ "source": [
+ "# !pip install gradio evaluate datasets\n",
+ "# !pip install accelerate -U\n",
+ "# !pip install git+https://github.com/huggingface/transformers"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 310,
+ "referenced_widgets": [
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+ "a950b654215e4defac5f3362fad52bd3",
+ "e0400f0834174e4fa947ef02373929b0",
+ "c47f3d7685e6476aa6021647bae767b7",
+ "c6c6c32e5b1e46c3bf74c0a100620a15",
+ "ce305f78898a4f1682ccc24c9768d9bc",
+ "63e5ba242ec8464c8b23c73679acc0e6",
+ "5f908f6a0a9047118cc8459016bef43b",
+ "c82118635df9483fb6d7e8a96d720c71",
+ "85b25b0aebb945c9b4275c43b5ff25b8"
+ ]
+ },
+ "id": "04RTpQVvnRrQ",
+ "outputId": "a329e439-771b-4a82-ee29-6ad302194a01"
+ },
+ "outputs": [],
+ "source": [
+ "from datasets import load_dataset\n",
+ "\n",
+ "gtzan = load_dataset(\"marsyas/gtzan\", \"all\")\n",
+ "gtzan"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "2uFZjfW0n6cE",
+ "outputId": "111b8376-927c-4d4f-b516-8941b0331453"
+ },
+ "outputs": [],
+ "source": [
+ "gtzan = gtzan[\"train\"].train_test_split(seed=42, shuffle=True, test_size=0.1)\n",
+ "gtzan"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "qBYE2mttoR7c",
+ "outputId": "f193c9de-8f0e-4dd0-d6ae-47540c76a2ca"
+ },
+ "outputs": [],
+ "source": [
+ "gtzan[\"train\"][0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 36
+ },
+ "id": "UDyiAFEwoeH9",
+ "outputId": "a17d65c1-0c88-4204-eb88-c22c03002a93"
+ },
+ "outputs": [],
+ "source": [
+ "id2label_fn = gtzan[\"train\"].features[\"genre\"].int2str\n",
+ "id2label_fn(gtzan[\"train\"][0][\"genre\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "ydaWOEJ2ohgR"
+ },
+ "outputs": [],
+ "source": [
+ "#from IPython.display import Audio as displayAudio\n",
+ "\n",
+ "#Audio(gtzan[\"train\"][0][\"audio\"][\"array\"], rate=gtzan[\"train\"][0][\"audio\"][\"sampling_rate\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "Q-GC0FqGozFR"
+ },
+ "outputs": [],
+ "source": [
+ "# import gradio as gr\n",
+ "# def generate_audio():\n",
+ "# example = gtzan[\"train\"].shuffle()[0]\n",
+ "# audio = example[\"audio\"]\n",
+ "# return (\n",
+ "# audio[\"sampling_rate\"],\n",
+ "# audio[\"array\"],\n",
+ "# ), id2label_fn(example[\"genre\"])\n",
+ "\n",
+ "\n",
+ "# with gr.Blocks() as demo:\n",
+ "# with gr.Column():\n",
+ "# for _ in range(4):\n",
+ "# audio, label = generate_audio()\n",
+ "# output = gr.Audio(audio, label=label)\n",
+ "\n",
+ "# demo.launch(debug=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
+ "6705d6a87ece43f38cb8b97aa7879a60",
+ "eeacae19074941dd86420224a9bc2a5a",
+ "16053dc329874fc69ca7e0341df95b5c",
+ "cd7fb99ef161430ebc5f81bb815e77a5",
+ "94b0305ca77b49cca01d3763bb7ee183",
+ "9bd72e05d99a4f62a0aefa17016e7523",
+ "97d062e85b2f426ea6c07d037014b804",
+ "8139dd6394ee46c3bbf78c4939d3e3f2",
+ "22724782e3fc4707bd16b2f1edf51854",
+ "a37b987f0c7a490e99c6d9aa8b515daf",
+ "9f3f4a59602348d5a1857747e7aeb856"
+ ]
+ },
+ "id": "otPBHNafpXbP",
+ "outputId": "9cb47552-0f63-49a9-c961-54b337bf5313"
+ },
+ "outputs": [],
+ "source": [
+ "from transformers import AutoFeatureExtractor\n",
+ "from transformers import AutoConfig\n",
+ "\n",
+ "model_id = \"ntu-spml/distilhubert\" #\"NicolasDenier/distilhubert-finetuned-gtzan\"\n",
+ "\n",
+ "configuration = AutoConfig.from_pretrained(model_id)\n",
+ "configuration.hidden_dropout = 0.5\n",
+ "configuration.attention_dropout = 0.1\n",
+ "\n",
+ "feature_extractor = AutoFeatureExtractor.from_pretrained(\n",
+ " model_id, do_normalize=True, return_attention_mask=True, config=configuration\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "AdN3TpY6qiZQ",
+ "outputId": "414653f2-5a1b-4417-d5c9-763869fa3c7f"
+ },
+ "outputs": [],
+ "source": [
+ "sampling_rate = feature_extractor.sampling_rate\n",
+ "sampling_rate"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "dvX22bjJql93",
+ "outputId": "d421b5b7-e4fc-446a-8c9c-f01ded406c97"
+ },
+ "outputs": [],
+ "source": [
+ "from datasets import Audio\n",
+ "\n",
+ "gtzan = gtzan.cast_column(\"audio\", Audio(sampling_rate=sampling_rate))\n",
+ "gtzan[\"train\"][0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "sm4p3J38JzgE"
+ },
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import librosa\n",
+ "import random\n",
+ "\n",
+ "test = gtzan[\"train\"][4]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "B8MuaIxmJ6L2"
+ },
+ "outputs": [],
+ "source": [
+ "def change_pitch(data, sampling_rate, pitch_factor):\n",
+ " data = np.asarray(data, dtype=np.float64)\n",
+ " augmented_data = librosa.effects.pitch_shift(data, sr=sampling_rate, n_steps=pitch_factor)\n",
+ " return augmented_data\n",
+ "\n",
+ "def add_noise(data, noise_factor):\n",
+ " data = np.asarray(data, dtype=np.float64)\n",
+ " noise = np.random.randn(len(data))\n",
+ " augmented_data = data + noise_factor * noise\n",
+ " # Cast back to same data type\n",
+ " augmented_data = augmented_data.astype(type(data[0]))\n",
+ " return augmented_data\n",
+ "\n",
+ "def transform_data(data, sr=16000):\n",
+ " # 1/2 chance of getting transformed\n",
+ " if random.random()>0.6:\n",
+ " data = np.asarray(data, dtype=np.float64)\n",
+ " # random pitch in [-4,-2]U[2,4]\n",
+ " pitch_factor = random.randint(2,4) *(1 if random.random()>0.5 else -1)\n",
+ " data_augmented = change_pitch(data, sr, pitch_factor)\n",
+ " # random noise in [0.05,0.2]\n",
+ " noise_factor = random.random()*0.15+0.05\n",
+ " data_augmented = add_noise(data_augmented, noise_factor)\n",
+ " return data_augmented\n",
+ " else:\n",
+ " return data\n",
+ "\n",
+ "transform_data_vect = np.vectorize(transform_data , signature='(n)->(n)')\n",
+ "\n",
+ "test_pitch = change_pitch(test[\"audio\"][\"array\"], sampling_rate, 8) # -4\n",
+ "test_noise = add_noise(test[\"audio\"][\"array\"], 0.2)\n",
+ "test_pitch_noise = transform_data(test[\"audio\"][\"array\"])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 75
+ },
+ "id": "M_f0MPCln2Et",
+ "outputId": "054a5bce-4be1-4b93-ca80-5745daff9769"
+ },
+ "outputs": [],
+ "source": [
+ "#displayAudio(test_pitch_noise, rate=sampling_rate)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "PxNhv2VwwUmU",
+ "outputId": "6c697a16-ac63-4c76-e651-13839588be04"
+ },
+ "outputs": [],
+ "source": [
+ "# sample = gtzan[\"train\"][0][\"audio\"]\n",
+ "\n",
+ "# print(f\"Mean: {np.mean(sample['array']):.3}, Variance: {np.var(sample['array']):.3}\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "t8elhfk0wjHd",
+ "outputId": "1512fee3-88e6-4bd5-90d4-fc2986f86cd6"
+ },
+ "outputs": [],
+ "source": [
+ "# inputs = feature_extractor(sample[\"array\"], sampling_rate=sample[\"sampling_rate\"])\n",
+ "\n",
+ "# print(f\"inputs keys: {list(inputs.keys())}\")\n",
+ "\n",
+ "# print(\n",
+ "# f\"Mean: {np.mean(inputs['input_values']):.3}, Variance: {np.var(inputs['input_values']):.3}\"\n",
+ "# )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "6TMGN7QZ7-ib"
+ },
+ "outputs": [],
+ "source": [
+ "max_duration = 30.0\n",
+ "\n",
+ "def preprocess_function(examples):\n",
+ " audio_arrays = [x[\"array\"] for x in examples[\"audio\"]]\n",
+ " inputs = feature_extractor(\n",
+ " audio_arrays,\n",
+ " sampling_rate=feature_extractor.sampling_rate,\n",
+ " max_length=int(feature_extractor.sampling_rate * max_duration),\n",
+ " truncation=True,\n",
+ " padding=True,\n",
+ " return_attention_mask=True,\n",
+ " )\n",
+ " return inputs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 198,
+ "referenced_widgets": [
+ "3b01e59f07154eb793df8233bc1d96c4",
+ "ad879fef94c749189bd835d53907e9df",
+ "935fa4de17fb40eea3000bc59683288a",
+ "cd7fe0cbbf1a4be7b469b46d2ad2e276",
+ "4f55f57600af4314b3ce38df83df035c",
+ "78d07d6fd0384f41862e83d1550106c6",
+ "117ba917e8ce4049bf92cf532554232f",
+ "f4b0f3131f5647a0af5bdcdf7df6178c",
+ "2b294112e4dd4ffd8c2d6b6bb69832ae",
+ "a9af3e0ccd6a4a68bd6183aae87cf80f",
+ "80e4ad1d047a4d979e42177ce76da0c8",
+ "32595b0affc543b7bd0e5f9f7d3c6175",
+ "7827050a570e4a68909d3b2527b0f481",
+ "e3c47febbc4a45958524ef933b0d9653",
+ "4c285d170b87458aa76104331c9424b4",
+ "43fd50cb51054e9a9176db438b5f20d4",
+ "4acd6a33d39245609c8167598473f706",
+ "2b90419190dc42d58d6352b1677a61c8",
+ "8fff1ac6ec164f5a87680f35d20ce94a",
+ "e5cf69820f6d43dab96703e75571161e",
+ "bed4cc07399f4796b61414a23fc06d4f",
+ "8d586a0b5e044b3f998e68daf00d0829"
+ ]
+ },
+ "id": "XDL7-anz8Gg2",
+ "outputId": "84758812-3e60-447f-d073-b299f2ce671a"
+ },
+ "outputs": [],
+ "source": [
+ "gtzan_encoded = gtzan.map(\n",
+ " preprocess_function, remove_columns=[\"audio\", \"file\"], batched=True, num_proc=1, batch_size=100\n",
+ ")\n",
+ "gtzan_encoded"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "FEzdivosy-c8"
+ },
+ "outputs": [],
+ "source": [
+ "gtzan_encoded = gtzan_encoded.rename_column(\"genre\", \"label\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import copy\n",
+ "# copy the test dataset to not apply tranformations on it\n",
+ "gtzan_encoded_test = copy.deepcopy(gtzan_encoded['test'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def transform_batch(batch):\n",
+ " augmented_data = transform_data_vect(batch[\"input_values\"])\n",
+ " augmented_batch = {'input_values': augmented_data}\n",
+ " return augmented_batch"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# define a function that will be called when the data is accessed\n",
+ "gtzan_encoded.set_transform(transform_batch, columns=\"input_values\", output_all_columns=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 36
+ },
+ "id": "Zmo_ia4LzOvw",
+ "outputId": "f91b3462-d2bd-48ba-9841-2a56071b45d9"
+ },
+ "outputs": [],
+ "source": [
+ "id2label = {\n",
+ " str(i): id2label_fn(i)\n",
+ " for i in range(len(gtzan_encoded[\"train\"].features[\"label\"].names))\n",
+ "}\n",
+ "label2id = {v: k for k, v in id2label.items()}\n",
+ "\n",
+ "id2label[\"7\"]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 137,
+ "referenced_widgets": [
+ "a3cbacbc3b1b40b3bd145df72a07a778",
+ "31e06327af634ef9a2e4476b454eaa58",
+ "a5e1affd81654c308e1e41d85b35f9ab",
+ "6bdc9b11334346e3bd19dc45dafc0e43",
+ "587082d7b0ad4c7fb985cb80c10fcb4a",
+ "6b62572975f44b579f0c45db436d7ab3",
+ "e6737f67833744ad81c7e777d4c00339",
+ "d4b7fd062f9441acb627ac78c40f3c53",
+ "92c5af5998a94f3789013c7b132a85da",
+ "abfff74215f04bc0ba792759d5741b0d",
+ "bc59e3149c384a1a862c2a2dbcdc5cb6",
+ "6590afcf2dd34bcb92e3dea7c03feeab",
+ "9de5fd6c3f384174a494fbc21063762e",
+ "150b7dc6d536416885a0feac36590d60",
+ "c3efdfb00ae4409c88af13eccc9feafc",
+ "4c30a61ec8ec49398fce28254d525c9e",
+ "f497c9b05ba7450699bb5249efdcdd78",
+ "d22bc41a3cc24a3b8af5a0b757a50772",
+ "8d2aaedb349740be9631a8d06dadaa0d",
+ "75aab13f7e3545bd8bfcaa93588be53d",
+ "38f925efe22c4e07ad4e26b43c77efbf",
+ "2965fd0946a240ccb2a107733892e2e3"
+ ]
+ },
+ "id": "jFjF5q2E0qyK",
+ "outputId": "a3fb48ec-2487-4fb9-d93c-dc993020a52d"
+ },
+ "outputs": [],
+ "source": [
+ "from transformers import AutoModelForAudioClassification\n",
+ "\n",
+ "num_labels = len(id2label)\n",
+ "\n",
+ "model = AutoModelForAudioClassification.from_pretrained(\n",
+ " model_id,\n",
+ " num_labels=num_labels,\n",
+ " label2id=label2id,\n",
+ " id2label=id2label,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 145,
+ "referenced_widgets": [
+ "8c23597b6abc4cf8b487cf766b49a6b2",
+ "1b52606d686449f9a77a5c5321ca9ce5",
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+ "7f671f9b13114c31982d15550a301308",
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+ "81d830c97454458b9a093b32429613c8",
+ "454ef1f88a2744e79e69e933834cade7",
+ "7314bc0da35f433e93adc61c741c1ad9",
+ "92b64987bf2843a89ae3fd239e2e929e",
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+ ]
+ },
+ "id": "R2dV29rf1Dvj",
+ "outputId": "d22284bc-b1e1-4f5f-81c3-1108d2548108"
+ },
+ "outputs": [],
+ "source": [
+ "from huggingface_hub import notebook_login\n",
+ "\n",
+ "notebook_login()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "Xxv5arIP1cyI"
+ },
+ "outputs": [],
+ "source": [
+ "from transformers import TrainingArguments\n",
+ "\n",
+ "model_name = \"distilhubert\"\n",
+ "batch_size = 8\n",
+ "gradient_accumulation_steps = 1\n",
+ "num_train_epochs = 12\n",
+ "\n",
+ "training_args = TrainingArguments(\n",
+ " f\"{model_name}-finetuned-gtzan\",\n",
+ " evaluation_strategy=\"epoch\",\n",
+ " save_strategy=\"epoch\",\n",
+ " learning_rate=5e-5,\n",
+ " per_device_train_batch_size=batch_size,\n",
+ " gradient_accumulation_steps=gradient_accumulation_steps,\n",
+ " per_device_eval_batch_size=batch_size,\n",
+ " num_train_epochs=num_train_epochs,\n",
+ " warmup_ratio=0.1,\n",
+ " logging_steps=5,\n",
+ " load_best_model_at_end=True,\n",
+ " metric_for_best_model=\"accuracy\",\n",
+ " fp16=True,\n",
+ " push_to_hub=True,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
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+ "outputId": "ca2ec7c8-80b0-4eea-98df-5ef644d818ae"
+ },
+ "outputs": [],
+ "source": [
+ "import evaluate\n",
+ "\n",
+ "metric = evaluate.load(\"accuracy\")\n",
+ "\n",
+ "def compute_metrics(eval_pred):\n",
+ " \"\"\"Computes accuracy on a batch of predictions\"\"\"\n",
+ " predictions = np.argmax(eval_pred.predictions, axis=1)\n",
+ " return metric.compute(predictions=predictions, references=eval_pred.label_ids)"
+ ]
+ },
+ {
+ "cell_type": "code",
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+ "colab": {
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+ },
+ "id": "7OwwlTZe17kG",
+ "outputId": "b6050257-ae63-42d7-a87e-14c5d631fd57"
+ },
+ "outputs": [],
+ "source": [
+ "from transformers import Trainer\n",
+ "\n",
+ "trainer = Trainer(\n",
+ " model,\n",
+ " training_args,\n",
+ " train_dataset=gtzan_encoded[\"train\"],\n",
+ " eval_dataset=gtzan_encoded_test,\n",
+ " tokenizer=feature_extractor,\n",
+ " compute_metrics=compute_metrics,\n",
+ ")\n",
+ "\n",
+ "trainer.train()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "ZYmItvzH3JUp"
+ },
+ "outputs": [],
+ "source": [
+ "kwargs = {\n",
+ " \"dataset_tags\": \"marsyas/gtzan\",\n",
+ " \"dataset\": \"GTZAN\",\n",
+ " \"model_name\": f\"{model_name}-finetuned-gtzan\",\n",
+ " \"finetuned_from\": model_id,\n",
+ " \"tasks\": \"audio-classification\",\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "BDzHhpmB3NW7"
+ },
+ "outputs": [],
+ "source": [
+ "trainer.push_to_hub(**kwargs)"
+ ]
+ }
+ ],
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+ "accelerator": "GPU",
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+ },
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