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+ "outputId": "9660457e-20fc-43c3-d907-3d79099740ca"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Mon Jan 24 03:58:42 2022 \n",
+ "+-----------------------------------------------------------------------------+\n",
+ "| NVIDIA-SMI 495.46 Driver Version: 460.32.03 CUDA Version: 11.2 |\n",
+ "|-------------------------------+----------------------+----------------------+\n",
+ "| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\n",
+ "| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\n",
+ "| | | MIG M. |\n",
+ "|===============================+======================+======================|\n",
+ "| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n",
+ "| N/A 56C P8 10W / 70W | 0MiB / 15109MiB | 0% Default |\n",
+ "| | | N/A |\n",
+ "+-------------------------------+----------------------+----------------------+\n",
+ " \n",
+ "+-----------------------------------------------------------------------------+\n",
+ "| Processes: |\n",
+ "| GPU GI CI PID Type Process name GPU Memory |\n",
+ "| ID ID Usage |\n",
+ "|=============================================================================|\n",
+ "| No running processes found |\n",
+ "+-----------------------------------------------------------------------------+\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "%%capture\n",
+ "!pip install -q datasets transformers\n",
+ "!pip install huggingface_hub\n",
+ "!pip install torchaudio\n",
+ "!pip install librosa\n",
+ "!pip install jiwer"
+ ],
+ "metadata": {
+ "id": "DtlJ3Ey1Bafu"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "!apt install git-lfs"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/"
+ },
+ "id": "OFHZExbKD82m",
+ "outputId": "83a32fd0-363e-40e4-9ad6-f4b3113fe476"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Reading package lists... Done\n",
+ "Building dependency tree \n",
+ "Reading state information... Done\n",
+ "The following NEW packages will be installed:\n",
+ " git-lfs\n",
+ "0 upgraded, 1 newly installed, 0 to remove and 37 not upgraded.\n",
+ "Need to get 2,129 kB of archives.\n",
+ "After this operation, 7,662 kB of additional disk space will be used.\n",
+ "Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 git-lfs amd64 2.3.4-1 [2,129 kB]\n",
+ "Fetched 2,129 kB in 1s (2,377 kB/s)\n",
+ "Selecting previously unselected package git-lfs.\n",
+ "(Reading database ... 155229 files and directories currently installed.)\n",
+ "Preparing to unpack .../git-lfs_2.3.4-1_amd64.deb ...\n",
+ "Unpacking git-lfs (2.3.4-1) ...\n",
+ "Setting up git-lfs (2.3.4-1) ...\n",
+ "Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from huggingface_hub import notebook_login\n",
+ "\n",
+ "notebook_login()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 359,
+ "referenced_widgets": [
+ "7278058e7f91448180f7e817413dbb31",
+ "fc59fca7658c49afa2743fd85aa6ef28",
+ "3d8f3821d8b54c139e6bd0be1a9070c5",
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+ "10c83c8849884e0dbfb52e996b53eb03",
+ "74236e8f309540a9b2dd1ae295ccda1e",
+ "a03ed455454941fc92851c34e636e479",
+ "43a486f5098c4f6da908ee74af58b65b",
+ "c7debde6880b499babc85fb43a5fcce0",
+ "33b6c66948b94924a8a4e9c9f3235fe8"
+ ]
+ },
+ "id": "GsGvBYj-aWkk",
+ "outputId": "63292a34-7d53-4a26-bdec-58f6acf2317e"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Login successful\n",
+ "Your token has been saved to /root/.huggingface/token\n",
+ "\u001b[1m\u001b[31mAuthenticated through git-credential store but this isn't the helper defined on your machine.\n",
+ "You might have to re-authenticate when pushing to the Hugging Face Hub. Run the following command in your terminal in case you want to set this credential helper as the default\n",
+ "\n",
+ "git config --global credential.helper store\u001b[0m\n"
+ ]
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from datasets import load_dataset, load_metric, Audio"
+ ],
+ "metadata": {
+ "id": "Zo8s-AlYDyCj"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "common_voice_train = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"pa-IN\", split=\"train+validation\", use_auth_token=True)\n",
+ "common_voice_test = load_dataset(\"mozilla-foundation/common_voice_7_0\", \"pa-IN\", split=\"test\", use_auth_token=True)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 197,
+ "referenced_widgets": [
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+ ]
+ },
+ "id": "0R2fwMfAD_oh",
+ "outputId": "cebdfb7b-b097-4ca7-a8d9-b37223159e10"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "4bdcddb6b60f4bb9bffc01ead12ab011",
+ "version_minor": 0,
+ "version_major": 2
+ },
+ "text/plain": [
+ "Downloading: 0%| | 0.00/9.79k [00:00 main\n",
+ "\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "application/vnd.google.colaboratory.intrinsic+json": {
+ "type": "string"
+ },
+ "text/plain": [
+ "'https://huggingface.co/anuragshas/wav2vec2-large-xls-r-300m-pa-in/commit/50e2ea63d2998b4c2877a0b6cda18c59a518a357'"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 26
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from transformers import Wav2Vec2FeatureExtractor\n",
+ "\n",
+ "feature_extractor = Wav2Vec2FeatureExtractor(feature_size=1, sampling_rate=16000, padding_value=0.0, do_normalize=True, return_attention_mask=True)"
+ ],
+ "metadata": {
+ "id": "pZMN1_9VFoR4"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "from transformers import Wav2Vec2Processor\n",
+ "\n",
+ "processor = Wav2Vec2Processor(feature_extractor=feature_extractor, tokenizer=tokenizer)"
+ ],
+ "metadata": {
+ "id": "OdqVLzfpFyak"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "common_voice_train = common_voice_train.cast_column(\"audio\", Audio(sampling_rate=16_000))\n",
+ "common_voice_test = common_voice_test.cast_column(\"audio\", Audio(sampling_rate=16_000))"
+ ],
+ "metadata": {
+ "id": "__QcVbmkF0ZD"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "def prepare_dataset(batch):\n",
+ " audio = batch[\"audio\"]\n",
+ "\n",
+ " # batched output is \"un-batched\"\n",
+ " batch[\"input_values\"] = processor(audio[\"array\"], sampling_rate=audio[\"sampling_rate\"]).input_values[0]\n",
+ " batch[\"input_length\"] = len(batch[\"input_values\"])\n",
+ " \n",
+ " with processor.as_target_processor():\n",
+ " batch[\"labels\"] = processor(batch[\"sentence\"]).input_ids\n",
+ " return batch"
+ ],
+ "metadata": {
+ "id": "XH83kfcIF2HI"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "common_voice_train = common_voice_train.map(prepare_dataset, remove_columns=common_voice_train.column_names)\n",
+ "common_voice_test = common_voice_test.map(prepare_dataset, remove_columns=common_voice_test.column_names)"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 81,
+ "referenced_widgets": [
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+ ]
+ },
+ "id": "K3eu7blnF4x1",
+ "outputId": "b70737db-4fc3-487c-bec5-e359fa702673"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "b50e08d9e0bf4f3c90bb608a3d6b1d50",
+ "version_minor": 0,
+ "version_major": 2
+ },
+ "text/plain": [
+ " 0%| | 0/781 [00:00 Dict[str, torch.Tensor]:\n",
+ " # split inputs and labels since they have to be of different lenghts and need\n",
+ " # different padding methods\n",
+ " input_features = [{\"input_values\": feature[\"input_values\"]} for feature in features]\n",
+ " label_features = [{\"input_ids\": feature[\"labels\"]} for feature in features]\n",
+ "\n",
+ " batch = self.processor.pad(\n",
+ " input_features,\n",
+ " padding=self.padding,\n",
+ " return_tensors=\"pt\",\n",
+ " )\n",
+ " with self.processor.as_target_processor():\n",
+ " labels_batch = self.processor.pad(\n",
+ " label_features,\n",
+ " padding=self.padding,\n",
+ " return_tensors=\"pt\",\n",
+ " )\n",
+ "\n",
+ " # replace padding with -100 to ignore loss correctly\n",
+ " labels = labels_batch[\"input_ids\"].masked_fill(labels_batch.attention_mask.ne(1), -100)\n",
+ "\n",
+ " batch[\"labels\"] = labels\n",
+ "\n",
+ " return batch"
+ ],
+ "metadata": {
+ "id": "bsKE5G8EF6nS"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "data_collator = DataCollatorCTCWithPadding(processor=processor, padding=True)"
+ ],
+ "metadata": {
+ "id": "pCAvRcS0F8qm"
+ },
+ "execution_count": null,
+ "outputs": []
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "wer_metric = load_metric(\"wer\")"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 49,
+ "referenced_widgets": [
+ "cca666050afa450a830b4180b86fbfa8",
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+ ]
+ },
+ "id": "i3VkPgBhF-OK",
+ "outputId": "ae458327-2e27-43f7-dced-30bfaba56174"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "cca666050afa450a830b4180b86fbfa8",
+ "version_minor": 0,
+ "version_major": 2
+ },
+ "text/plain": [
+ "Downloading: 0%| | 0.00/1.91k [00:00\n",
+ " \n",
+ " \n",
+ " [2880/2880 3:13:48, Epoch 119/120]\n",
+ " \n",
+ " \n",
+ " \n",
+ " \n",
+ " | Step | \n",
+ " Training Loss | \n",
+ " Validation Loss | \n",
+ " Wer | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 400 | \n",
+ " 6.480400 | \n",
+ " 1.846061 | \n",
+ " 1.000000 | \n",
+ "
\n",
+ " \n",
+ " | 800 | \n",
+ " 0.474000 | \n",
+ " 1.101765 | \n",
+ " 0.662428 | \n",
+ "
\n",
+ " \n",
+ " | 1200 | \n",
+ " 0.138900 | \n",
+ " 1.191819 | \n",
+ " 0.610336 | \n",
+ "
\n",
+ " \n",
+ " | 1600 | \n",
+ " 0.091900 | \n",
+ " 1.188941 | \n",
+ " 0.605824 | \n",
+ "
\n",
+ " \n",
+ " | 2000 | \n",
+ " 0.065700 | \n",
+ " 1.226577 | \n",
+ " 0.593109 | \n",
+ "
\n",
+ " \n",
+ " | 2400 | \n",
+ " 0.047900 | \n",
+ " 1.251161 | \n",
+ " 0.590238 | \n",
+ "
\n",
+ " \n",
+ " | 2800 | \n",
+ " 0.035500 | \n",
+ " 1.254808 | \n",
+ " 0.567678 | \n",
+ "
\n",
+ " \n",
+ "
"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {}
+ },
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
+ "***** Running Evaluation *****\n",
+ " Num examples = 343\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-pa-in/checkpoint-400\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-400/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-400/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-400/preprocessor_config.json\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/preprocessor_config.json\n",
+ "/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1093: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
+ " return (input_length - kernel_size) // stride + 1\n",
+ "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
+ "***** Running Evaluation *****\n",
+ " Num examples = 343\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-pa-in/checkpoint-800\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-800/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-800/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-800/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-pa-in/checkpoint-400] due to args.save_total_limit\n",
+ "/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1093: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
+ " return (input_length - kernel_size) // stride + 1\n",
+ "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
+ "***** Running Evaluation *****\n",
+ " Num examples = 343\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-pa-in/checkpoint-1200\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-1200/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-1200/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-1200/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-pa-in/checkpoint-800] due to args.save_total_limit\n",
+ "/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1093: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
+ " return (input_length - kernel_size) // stride + 1\n",
+ "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
+ "***** Running Evaluation *****\n",
+ " Num examples = 343\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-pa-in/checkpoint-1600\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-1600/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-1600/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-1600/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-pa-in/checkpoint-1200] due to args.save_total_limit\n",
+ "/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1093: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
+ " return (input_length - kernel_size) // stride + 1\n",
+ "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
+ "***** Running Evaluation *****\n",
+ " Num examples = 343\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-pa-in/checkpoint-2000\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2000/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2000/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2000/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-pa-in/checkpoint-1600] due to args.save_total_limit\n",
+ "/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1093: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
+ " return (input_length - kernel_size) // stride + 1\n",
+ "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
+ "***** Running Evaluation *****\n",
+ " Num examples = 343\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-pa-in/checkpoint-2400\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2400/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2400/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2400/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-pa-in/checkpoint-2000] due to args.save_total_limit\n",
+ "/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1093: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
+ " return (input_length - kernel_size) // stride + 1\n",
+ "The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
+ "***** Running Evaluation *****\n",
+ " Num examples = 343\n",
+ " Batch size = 8\n",
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-pa-in/checkpoint-2800\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2800/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2800/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/checkpoint-2800/preprocessor_config.json\n",
+ "Deleting older checkpoint [wav2vec2-large-xls-r-300m-pa-in/checkpoint-2400] due to args.save_total_limit\n",
+ "/usr/local/lib/python3.7/dist-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1093: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').\n",
+ " return (input_length - kernel_size) // stride + 1\n",
+ "\n",
+ "\n",
+ "Training completed. Do not forget to share your model on huggingface.co/models =)\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "text/plain": [
+ "TrainOutput(global_step=2880, training_loss=1.0195181330045064, metrics={'train_runtime': 11634.7947, 'train_samples_per_second': 8.055, 'train_steps_per_second': 0.248, 'total_flos': 1.4789924329646787e+19, 'train_loss': 1.0195181330045064, 'epoch': 119.98})"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 41
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ "trainer.push_to_hub()"
+ ],
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 370,
+ "referenced_widgets": [
+ "115fbb1c21b145618fc0d391e201f922",
+ "d30c33ce5b674dd583cb880197136fad",
+ "e0810a85c656407d935c4959c29c52a5",
+ "092a6ab3acac4c22ad6dc15777ab031e",
+ "14b5af3cbe594ff282ae0415ae8e6d18",
+ "a8bd35737fd4472b98494d6b048ae119",
+ "997561dd68bb418ea86d6c957f919bfa",
+ "e7ec33dd62df4063bb6d0abd3c8c1aa6",
+ "d9cc3eaea19644f1baafabb4cf52f8f0",
+ "93eb52140f654537be2b64c045a0d65b",
+ "710fc56bc545449da082a953769a5a92",
+ "81557dc72fbb4a18b2207e61acf83968",
+ "fd36cbd237054c569438ecce05d20120",
+ "9516bb75b27841629f9bb735a5240c5a",
+ "a35b729be41f4b11bb8e4d94541476ba",
+ "4112dded89304231b1438af48e7bb9ec",
+ "1f5913397eb14f5c9226af6a864df7e5",
+ "13ae6e7ece3049ecb241c3cc94fb279c",
+ "25efb9576ecf4d3eaab3125b5d1c7c20",
+ "7eba46668fad435c8ae8fee539e1f961",
+ "aa32eeb3e38a44b09f87125be320f1b3",
+ "780bf497ebad453c98d48f8a73c71c4e"
+ ]
+ },
+ "id": "ocBhbxkrGN5A",
+ "outputId": "b1ddc7c5-10ad-49ab-dc0b-a49771bd7b8f"
+ },
+ "execution_count": null,
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stderr",
+ "text": [
+ "Saving model checkpoint to wav2vec2-large-xls-r-300m-pa-in\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/config.json\n",
+ "Model weights saved in wav2vec2-large-xls-r-300m-pa-in/pytorch_model.bin\n",
+ "Configuration saved in wav2vec2-large-xls-r-300m-pa-in/preprocessor_config.json\n",
+ "Several commits (2) will be pushed upstream.\n",
+ "The progress bars may be unreliable.\n"
+ ]
+ },
+ {
+ "output_type": "display_data",
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "115fbb1c21b145618fc0d391e201f922",
+ "version_minor": 0,
+ "version_major": 2
+ },
+ "text/plain": [
+ "Upload file pytorch_model.bin: 0%| | 3.37k/1.18G [00:00 main\n",
+ "\n",
+ "Dropping the following result as it does not have all the necessary fields:\n",
+ "{'dataset': {'name': 'common_voice', 'type': 'common_voice', 'args': 'pa-IN'}}\n",
+ "To https://huggingface.co/anuragshas/wav2vec2-large-xls-r-300m-pa-in\n",
+ " 1cdd79d..8e03b20 main -> main\n",
+ "\n"
+ ]
+ },
+ {
+ "output_type": "execute_result",
+ "data": {
+ "application/vnd.google.colaboratory.intrinsic+json": {
+ "type": "string"
+ },
+ "text/plain": [
+ "'https://huggingface.co/anuragshas/wav2vec2-large-xls-r-300m-pa-in/commit/1cdd79df0dfa4f2075b214fcad940488dea7edf2'"
+ ]
+ },
+ "metadata": {},
+ "execution_count": 42
+ }
+ ]
+ },
+ {
+ "cell_type": "code",
+ "source": [
+ ""
+ ],
+ "metadata": {
+ "id": "2Lyjc1qQHB37"
+ },
+ "execution_count": null,
+ "outputs": []
+ }
+ ]
+}
\ No newline at end of file