1825 lines
158 KiB
Plaintext
1825 lines
158 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"id": "8d07f027",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Using custom data configuration default-8f1be135afea2a5e\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Downloading and preparing dataset json/default to /workspace/.cache/huggingface/datasets/json/default-8f1be135afea2a5e/0.0.0/ac0ca5f5289a6cf108e706efcf040422dbbfa8e658dee6a819f20d76bb84d26b...\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "1b68f3c845a14540b7fa4feb0b78d3e9",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "54002c8dc2044b3987377cf519579109",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Dataset json downloaded and prepared to /workspace/.cache/huggingface/datasets/json/default-8f1be135afea2a5e/0.0.0/ac0ca5f5289a6cf108e706efcf040422dbbfa8e658dee6a819f20d76bb84d26b. Subsequent calls will reuse this data.\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "861f78e0c3b3458faa9cc42cde173d84",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Using custom data configuration default-cb03ad945d4a24ac\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Downloading and preparing dataset json/default to /workspace/.cache/huggingface/datasets/json/default-cb03ad945d4a24ac/0.0.0/ac0ca5f5289a6cf108e706efcf040422dbbfa8e658dee6a819f20d76bb84d26b...\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "f61b1f0086c340f9a8b2d9f20a08e0c1",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "7d18344e823a4848a9b98cfdec90b2ce",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Dataset json downloaded and prepared to /workspace/.cache/huggingface/datasets/json/default-cb03ad945d4a24ac/0.0.0/ac0ca5f5289a6cf108e706efcf040422dbbfa8e658dee6a819f20d76bb84d26b. Subsequent calls will reuse this data.\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "77bc9aad0b494696942e0fbd0663a29c",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Using custom data configuration default-eec7a48f9eca7cd5\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Downloading and preparing dataset json/default to /workspace/.cache/huggingface/datasets/json/default-eec7a48f9eca7cd5/0.0.0/ac0ca5f5289a6cf108e706efcf040422dbbfa8e658dee6a819f20d76bb84d26b...\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "200634fba7454dc5a611c6a79855bc42",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "d2246049976343659ce829d6c1f1e42e",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Dataset json downloaded and prepared to /workspace/.cache/huggingface/datasets/json/default-eec7a48f9eca7cd5/0.0.0/ac0ca5f5289a6cf108e706efcf040422dbbfa8e658dee6a819f20d76bb84d26b. Subsequent calls will reuse this data.\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "43219229d82c4e2a9d3cb916d1b56801",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?it/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'audio': {'path': '/workspace/data/ovm/ovm_111218-621.wav',\n",
|
||
" 'array': array([ 0.00079346, 0.00073242, 0.00012207, ..., -0.00323486,\n",
|
||
" -0.00177002, -0.00180054], dtype=float32),\n",
|
||
" 'sampling_rate': 16000},\n",
|
||
" 'sentence': 'co by novinář když václav havel byl v prezidentském úřadu a pak právě při psaní knížky prosím stručně vaše vzpomínka na václava havla'}"
|
||
]
|
||
},
|
||
"execution_count": 1,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import datasets\n",
|
||
"\n",
|
||
"def load_local_dataset(dsname):\n",
|
||
" d = datasets.load_dataset('json', data_files=f'/workspace/data/{dsname}.json')\n",
|
||
" d = d.cast_column('audio', datasets.features.Audio(sampling_rate=16000))\n",
|
||
" return d\n",
|
||
"\n",
|
||
"ovm = load_local_dataset('ovm')\n",
|
||
"vyst = load_local_dataset('vystadial2016')\n",
|
||
"pscr = load_local_dataset('pscr')\n",
|
||
"\n",
|
||
"ovm['train'][0]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"id": "890ba811",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/cs/8.0.0/b8bc4d453193c06a43269b46cd87f075c70f152ac963b7f28f7a2760c45ec3e8)\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'path': 'cv-corpus-8.0-2022-01-19/cs/clips/common_voice_cs_20500740.mp3',\n",
|
||
" 'audio': {'path': 'cv-corpus-8.0-2022-01-19/cs/clips/common_voice_cs_20500740.mp3',\n",
|
||
" 'array': array([0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ..., 6.3757376e-05,\n",
|
||
" 4.1789750e-05, 6.2637460e-05], dtype=float32),\n",
|
||
" 'sampling_rate': 16000},\n",
|
||
" 'sentence': 'To dělá to, že se tady chodí po lukách místo po cestičkách.'}"
|
||
]
|
||
},
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"cv = datasets.load_dataset(\"mozilla-foundation/common_voice_8_0\", \"cs\", split=\"train+validation\", use_auth_token=True)\n",
|
||
"cv = cv.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"segment\", \"up_votes\"])\n",
|
||
"cv = cv.cast_column(\"audio\", datasets.Audio(sampling_rate=16_000))\n",
|
||
"cv[0]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 3,
|
||
"id": "3855ccb3",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'audio': {'path': '/workspace/data/vystadial2016/train/10/62/vad-2015-09-20--12-34-27.561625.wav',\n",
|
||
" 'array': array([ 0.00564575, 0.00588989, 0.00363159, ..., -0.01358032,\n",
|
||
" -0.01220703, -0.00946045], dtype=float32),\n",
|
||
" 'sampling_rate': 16000},\n",
|
||
" 'sentence': 'olomouc hlavní nádraží',\n",
|
||
" 'path': None}"
|
||
]
|
||
},
|
||
"execution_count": 3,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"#all = datasets.interleave_datasets([ovm['train'], vyst['train'], pscr['train'], cv])\n",
|
||
"all = datasets.concatenate_datasets([ovm['train'], vyst['train'], pscr['train'], cv]).shuffle()\n",
|
||
"all[0]\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 4,
|
||
"id": "7c896f08",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Reusing dataset common_voice (/workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/cs/8.0.0/b8bc4d453193c06a43269b46cd87f075c70f152ac963b7f28f7a2760c45ec3e8)\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"7267"
|
||
]
|
||
},
|
||
"execution_count": 4,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"common_voice_test = datasets.load_dataset(\"mozilla-foundation/common_voice_8_0\", \"cs\", split=\"test\", use_auth_token=True)\n",
|
||
"common_voice_test = common_voice_test.remove_columns([\"accent\", \"age\", \"client_id\", \"down_votes\", \"gender\", \"locale\", \"segment\", \"up_votes\"])\n",
|
||
"len(common_voice_test)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "2eb3eb20",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"id": "f43b8d3d",
|
||
"metadata": {
|
||
"id": "ZcVsD0ETElrR"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import re\n",
|
||
"chars_to_remove_regex = '[\\,\\?\\.\\!\\-\\;\\:\\/\\\"\\“\\„\\%\\”\\<5C>\\–\\'\\`\\«\\»\\—\\’\\…]'\n",
|
||
"\n",
|
||
"\n",
|
||
"CHARS = {\n",
|
||
" 'ü': 'ue',\n",
|
||
" 'ö': 'oe',\n",
|
||
" 'ï': 'i',\n",
|
||
" 'ë': 'e',\n",
|
||
" 'ä': 'ae',\n",
|
||
" 'ã': 'a',\n",
|
||
" 'à': 'á',\n",
|
||
" 'ø': 'o',\n",
|
||
" 'è': 'é',\n",
|
||
" 'ê': 'é',\n",
|
||
" 'å': 'ó',\n",
|
||
" 'î': 'i',\n",
|
||
" 'ñ': 'ň',\n",
|
||
" 'ç': 's',\n",
|
||
" 'ľ': 'l',\n",
|
||
" 'ż': 'ž',\n",
|
||
" 'ł': 'w',\n",
|
||
" 'ć': 'č',\n",
|
||
" 'þ': 't',\n",
|
||
" 'ß': 'ss',\n",
|
||
" 'ę': 'en',\n",
|
||
" 'ą': 'an',\n",
|
||
" 'æ': 'ae',\n",
|
||
" }\n",
|
||
"\n",
|
||
"def replace_chars(sentence):\n",
|
||
" result = ''\n",
|
||
" for ch in sentence:\n",
|
||
" new = CHARS[ch] if ch in CHARS else ch\n",
|
||
" result += new\n",
|
||
"\n",
|
||
" return result\n",
|
||
"\n",
|
||
"\n",
|
||
"def remove_special_characters(batch):\n",
|
||
" batch[\"sentence\"] = re.sub(chars_to_remove_regex, ' ', batch[\"sentence\"]).lower()\n",
|
||
" batch[\"sentence\"] = replace_chars(batch['sentence'])\n",
|
||
" batch[\"sentence\"] = \" \".join([char for char in batch[\"sentence\"].split(\" \") if char != \"\"])\n",
|
||
" return batch\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "d1fd4858",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "10a4628ef8454147a54a6d97fefe3532",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"0ex [00:00, ?ex/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Loading cached processed dataset at /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/cs/8.0.0/b8bc4d453193c06a43269b46cd87f075c70f152ac963b7f28f7a2760c45ec3e8/cache-900ef796264993e5.arrow\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"all = all.map(remove_special_characters)\n",
|
||
"common_voice_test = common_voice_test.map(remove_special_characters)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "ffb2e6ba",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "9acd28b1",
|
||
"metadata": {
|
||
"id": "LwCshNbbeRZR"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def extract_all_chars(batch):\n",
|
||
" all_text = \" \".join(batch[\"sentence\"])\n",
|
||
" vocab = list(set(all_text))\n",
|
||
" return {\"vocab\": [vocab], \"all_text\": [all_text]}"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "c009de89",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "d7103c4475a9464cb7dd5c66a68ddbf7",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
" 0%| | 0/1 [00:00<?, ?ba/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{' ': 0,\n",
|
||
" 'a': 1,\n",
|
||
" 'b': 2,\n",
|
||
" 'c': 3,\n",
|
||
" 'd': 4,\n",
|
||
" 'e': 5,\n",
|
||
" 'f': 6,\n",
|
||
" 'g': 7,\n",
|
||
" 'h': 8,\n",
|
||
" 'i': 9,\n",
|
||
" 'j': 10,\n",
|
||
" 'k': 11,\n",
|
||
" 'l': 12,\n",
|
||
" 'm': 13,\n",
|
||
" 'n': 14,\n",
|
||
" 'o': 15,\n",
|
||
" 'p': 16,\n",
|
||
" 'q': 17,\n",
|
||
" 'r': 18,\n",
|
||
" 's': 19,\n",
|
||
" 't': 20,\n",
|
||
" 'u': 21,\n",
|
||
" 'v': 22,\n",
|
||
" 'w': 23,\n",
|
||
" 'x': 24,\n",
|
||
" 'y': 25,\n",
|
||
" 'z': 26,\n",
|
||
" 'á': 27,\n",
|
||
" 'é': 28,\n",
|
||
" 'í': 29,\n",
|
||
" 'ó': 30,\n",
|
||
" 'ú': 31,\n",
|
||
" 'ý': 32,\n",
|
||
" 'č': 33,\n",
|
||
" 'ď': 34,\n",
|
||
" 'ě': 35,\n",
|
||
" 'ň': 36,\n",
|
||
" 'ř': 37,\n",
|
||
" 'š': 38,\n",
|
||
" 'ť': 39,\n",
|
||
" 'ů': 40,\n",
|
||
" 'ž': 41}"
|
||
]
|
||
},
|
||
"execution_count": 8,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"vocab_train = all.map(extract_all_chars, batched=True, batch_size=-1, keep_in_memory=True, remove_columns=all.column_names)\n",
|
||
"vocab_list = list(set(vocab_train[\"vocab\"][0]))\n",
|
||
"vocab_dict = {v: k for k, v in enumerate(sorted(vocab_list))}\n",
|
||
"vocab_dict"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"id": "7b237346",
|
||
"metadata": {
|
||
"id": "npbIbBoLgaFX"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"44"
|
||
]
|
||
},
|
||
"execution_count": 9,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"vocab_dict[\"|\"] = vocab_dict[\" \"]\n",
|
||
"del vocab_dict[\" \"]\n",
|
||
"vocab_dict[\"[UNK]\"] = len(vocab_dict)\n",
|
||
"vocab_dict[\"[PAD]\"] = len(vocab_dict)\n",
|
||
"len(vocab_dict)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"id": "a08bda02",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/workspace/cs/cs2\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"'/workspace/cs/cs2'"
|
||
]
|
||
},
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"%cd ~/cs/cs2\n",
|
||
"%pwd"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "154e541c",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"id": "411e1255",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "znF0bNunsjbl",
|
||
"outputId": "6b335aef-870c-41fc-98c9-664a357e5ab8"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"44"
|
||
]
|
||
},
|
||
"execution_count": 11,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"vocab_dict[\"[UNK]\"] = len(vocab_dict)\n",
|
||
"vocab_dict[\"[PAD]\"] = len(vocab_dict)\n",
|
||
"len(vocab_dict)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "e3f0c2f5",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 12,
|
||
"id": "8ab39e55",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 53
|
||
},
|
||
"id": "xriFGEWQkO4M",
|
||
"outputId": "a782d2e0-723d-464e-d3f6-577454322862"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from transformers import Wav2Vec2CTCTokenizer\n",
|
||
"\n",
|
||
"tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(\"./\", unk_token=\"[UNK]\", pad_token=\"[PAD]\", word_delimiter_token=\"|\")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 13,
|
||
"id": "5c1c8b06",
|
||
"metadata": {
|
||
"id": "A1XApZBAF2zr"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"repo_name = \"wav2vec2-xls-r-300m-cs-250\""
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"id": "b4b326f8",
|
||
"metadata": {
|
||
"id": "kAR0-2KLkopp"
|
||
},
|
||
"outputs": [],
|
||
"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)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"id": "30a92bc9",
|
||
"metadata": {
|
||
"id": "KYZtoW-tlZgl"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from transformers import Wav2Vec2Processor\n",
|
||
"\n",
|
||
"processor = Wav2Vec2Processor(feature_extractor=feature_extractor, tokenizer=tokenizer)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 16,
|
||
"id": "de95a6dc",
|
||
"metadata": {
|
||
"id": "kMv1VGCJoX8D"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# save tokenizer to folder\n",
|
||
"processor.save_pretrained(repo_name)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "6369313a",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 54
|
||
},
|
||
"id": "TTCS7W6XJ9BG",
|
||
"outputId": "d6a300c2-7b44-455b-8743-cb3088cab9b3"
|
||
},
|
||
"outputs": [],
|
||
"source": []
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 17,
|
||
"id": "d74c0b80",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 54
|
||
},
|
||
"id": "TTCS7W6XJ9BG",
|
||
"outputId": "d6a300c2-7b44-455b-8743-cb3088cab9b3"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"all[0][\"path\"]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 18,
|
||
"id": "a8b4ce20",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "qj_z5Zc3GAs9",
|
||
"outputId": "6e80ea55-bda2-41aa-d00f-d61f4803bf0a"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'path': '/workspace/data/vystadial2016/train/10/62/vad-2015-09-20--12-34-27.561625.wav',\n",
|
||
" 'array': array([ 0.00564575, 0.00588989, 0.00363159, ..., -0.01358032,\n",
|
||
" -0.01220703, -0.00946045], dtype=float32),\n",
|
||
" 'sampling_rate': 16000}"
|
||
]
|
||
},
|
||
"execution_count": 18,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"all[0][\"audio\"]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"id": "8a006882",
|
||
"metadata": {
|
||
"id": "rrv65aj7G95i"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from datasets import Audio\n",
|
||
"all = all.cast_column(\"audio\", Audio(sampling_rate=16_000))\n",
|
||
"common_voice_test = common_voice_test.cast_column(\"audio\", Audio(sampling_rate=16_000))"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"id": "fc328f00",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "aKtkc1o_HWHC",
|
||
"outputId": "3f36307e-777d-4937-884d-d4aab658bc1b"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'path': '/workspace/data/vystadial2016/train/10/62/vad-2015-09-20--12-34-27.561625.wav',\n",
|
||
" 'array': array([ 0.00564575, 0.00588989, 0.00363159, ..., -0.01358032,\n",
|
||
" -0.01220703, -0.00946045], dtype=float32),\n",
|
||
" 'sampling_rate': 16000}"
|
||
]
|
||
},
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"all[0][\"audio\"]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"id": "14fc4dc7",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 93
|
||
},
|
||
"id": "dueM6U7Ev0OA",
|
||
"outputId": "3f83e83a-139b-484c-8337-5df6dbe734a4"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"dobrý den chtěl bych jet\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"\n",
|
||
" <audio controls=\"controls\" autoplay=\"autoplay\">\n",
|
||
" <source src=\"data:audio/wav;base64,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\" type=\"audio/wav\" />\n",
|
||
" Your browser does not support the audio element.\n",
|
||
" </audio>\n",
|
||
" "
|
||
],
|
||
"text/plain": [
|
||
"<IPython.lib.display.Audio object>"
|
||
]
|
||
},
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import IPython.display as ipd\n",
|
||
"import numpy as np\n",
|
||
"import random\n",
|
||
"\n",
|
||
"rand_int = random.randint(0, len(all)-1)\n",
|
||
"\n",
|
||
"print(all[rand_int][\"sentence\"])\n",
|
||
"ipd.Audio(data=all[rand_int][\"audio\"][\"array\"], autoplay=True, rate=16000)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"id": "5607b522",
|
||
"metadata": {
|
||
"id": "eJY7I0XAwe9p"
|
||
},
|
||
"outputs": [],
|
||
"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"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"id": "00e34422",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 81,
|
||
"referenced_widgets": [
|
||
"c47ea368dd08403aa09b2bafdbb4b580",
|
||
"e77cf973d5824ae7b89bafd814805c2a",
|
||
"071b7647e1fe49609a48e4281a9efd0f",
|
||
"c97c00fcf2e64f18b637337f9244d748",
|
||
"9ca82fa27d1043e9ac9f10301e0b33bc",
|
||
"cc6c7e9931c140db8ba7a977c4461ce5",
|
||
"d207784bda7e4dd8858170f470ae2833",
|
||
"0800fef7de6e45d380873f974882d67e",
|
||
"926440595aa44c698588e02b86eb8c4c",
|
||
"ea2806c776384f1a90e36b72c2c17a44",
|
||
"6b72385c07134782995fcd76e675da7c",
|
||
"3653b92c9f2a408eac253e1d5153daf4",
|
||
"73ffd9b8166c4ec78ff2b62d17690327",
|
||
"6b133a1e11e44f68846ff931446559cf",
|
||
"7c98818547c84af7ba9284bc20101691",
|
||
"41b501a16b2a4f709197af5cdd5227cb",
|
||
"3b4fbe2916894e48b8f93ca63e203aca",
|
||
"c002386685c0413d8181b054d3f9d49f",
|
||
"cfb70829b5e1461abcb01872b74a194c",
|
||
"ed943db2b5274022a606ce4103d54425",
|
||
"cfb242eb549c4e66afcedefb575b4e38",
|
||
"a0313055d29f4a60837e59ac4d8a3870"
|
||
]
|
||
},
|
||
"id": "-np9xYK-wl8q",
|
||
"outputId": "573f6f67-e5b2-4977-a564-3919e7903592"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"application/vnd.jupyter.widget-view+json": {
|
||
"model_id": "45634e805c76453a94ffac3f287df33f",
|
||
"version_major": 2,
|
||
"version_minor": 0
|
||
},
|
||
"text/plain": [
|
||
"0ex [00:00, ?ex/s]"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Loading cached processed dataset at /workspace/.cache/huggingface/datasets/mozilla-foundation___common_voice/cs/8.0.0/b8bc4d453193c06a43269b46cd87f075c70f152ac963b7f28f7a2760c45ec3e8/cache-fcc378c48562cf8c.arrow\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"all = all.map(prepare_dataset, remove_columns=all.column_names)\n",
|
||
"common_voice_test = common_voice_test.map(prepare_dataset, remove_columns=common_voice_test.column_names)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"id": "4207ffd0",
|
||
"metadata": {
|
||
"id": "tborvC9hx88e"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"import torch\n",
|
||
"\n",
|
||
"from dataclasses import dataclass, field\n",
|
||
"from typing import Any, Dict, List, Optional, Union\n",
|
||
"\n",
|
||
"@dataclass\n",
|
||
"class DataCollatorCTCWithPadding:\n",
|
||
" \"\"\"\n",
|
||
" Data collator that will dynamically pad the inputs received.\n",
|
||
" Args:\n",
|
||
" processor (:class:`~transformers.Wav2Vec2Processor`)\n",
|
||
" The processor used for proccessing the data.\n",
|
||
" padding (:obj:`bool`, :obj:`str` or :class:`~transformers.tokenization_utils_base.PaddingStrategy`, `optional`, defaults to :obj:`True`):\n",
|
||
" Select a strategy to pad the returned sequences (according to the model's padding side and padding index)\n",
|
||
" among:\n",
|
||
" * :obj:`True` or :obj:`'longest'`: Pad to the longest sequence in the batch (or no padding if only a single\n",
|
||
" sequence if provided).\n",
|
||
" * :obj:`'max_length'`: Pad to a maximum length specified with the argument :obj:`max_length` or to the\n",
|
||
" maximum acceptable input length for the model if that argument is not provided.\n",
|
||
" * :obj:`False` or :obj:`'do_not_pad'` (default): No padding (i.e., can output a batch with sequences of\n",
|
||
" different lengths).\n",
|
||
" \"\"\"\n",
|
||
"\n",
|
||
" processor: Wav2Vec2Processor\n",
|
||
" padding: Union[bool, str] = True\n",
|
||
"\n",
|
||
" def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> 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"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"id": "2b346d91",
|
||
"metadata": {
|
||
"id": "lbQf5GuZyQ4_"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"data_collator = DataCollatorCTCWithPadding(processor=processor, padding=True)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 26,
|
||
"id": "3afc8d2a",
|
||
"metadata": {
|
||
"id": "9Xsux2gmyXso"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from datasets import load_metric\n",
|
||
"\n",
|
||
"wer_metric = load_metric(\"wer\")\n",
|
||
"cer_metric = load_metric(\"cer\")\n",
|
||
"metrics = [wer_metric, cer_metric]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"id": "9119abc6",
|
||
"metadata": {
|
||
"id": "1XZ-kjweyTy_"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"def compute_metrics(pred):\n",
|
||
" pred_logits = pred.predictions\n",
|
||
" pred_ids = np.argmax(pred_logits, axis=-1)\n",
|
||
"\n",
|
||
" pred.label_ids[pred.label_ids == -100] = processor.tokenizer.pad_token_id\n",
|
||
"\n",
|
||
" pred_str = processor.batch_decode(pred_ids)\n",
|
||
" # we do not want to group tokens when computing the metrics\n",
|
||
" label_str = processor.batch_decode(pred.label_ids, group_tokens=False)\n",
|
||
"\n",
|
||
" wer = wer_metric.compute(predictions=pred_str, references=label_str)\n",
|
||
" cer = cer_metric.compute(predictions=pred_str, references=label_str)\n",
|
||
"\n",
|
||
" return {\"wer\": wer, \"cer\": cer}"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 28,
|
||
"id": "172587ca",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "e7cqAWIayn6w",
|
||
"outputId": "7a7ef020-bc8f-41e2-846c-645be598312e"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Some weights of the model checkpoint at facebook/wav2vec2-xls-r-300m were not used when initializing Wav2Vec2ForCTC: ['project_hid.bias', 'project_q.weight', 'quantizer.weight_proj.bias', 'project_hid.weight', 'quantizer.weight_proj.weight', 'project_q.bias', 'quantizer.codevectors']\n",
|
||
"- This IS expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
|
||
"- This IS NOT expected if you are initializing Wav2Vec2ForCTC from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
|
||
"Some weights of Wav2Vec2ForCTC were not initialized from the model checkpoint at facebook/wav2vec2-xls-r-300m and are newly initialized: ['lm_head.weight', 'lm_head.bias']\n",
|
||
"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from transformers import Wav2Vec2ForCTC\n",
|
||
"\n",
|
||
"model = Wav2Vec2ForCTC.from_pretrained(\n",
|
||
" #\"comodoro/wav2vec2-xls-r-300m-cs-cv8\", \n",
|
||
" \"facebook/wav2vec2-xls-r-300m\", \n",
|
||
" attention_dropout=0.1,\n",
|
||
" hidden_dropout=0.2,\n",
|
||
" feat_proj_dropout=0.0,\n",
|
||
" mask_time_prob=0.1,\n",
|
||
" layerdrop=0.1,\n",
|
||
" ctc_loss_reduction=\"mean\", \n",
|
||
" pad_token_id=processor.tokenizer.pad_token_id,\n",
|
||
" vocab_size=len(processor.tokenizer),\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 29,
|
||
"id": "94625b79",
|
||
"metadata": {
|
||
"id": "oGI8zObtZ3V0"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/workspace/.local/lib/python3.8/site-packages/transformers/models/wav2vec2/modeling_wav2vec2.py:1700: FutureWarning: The method `freeze_feature_extractor` is deprecated and will be removed in Transformers v5.Please use the equivalent `freeze_feature_encoder` method instead.\n",
|
||
" warnings.warn(\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"model.freeze_feature_extractor()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"id": "9c173ad4",
|
||
"metadata": {
|
||
"id": "KbeKSV7uzGPP"
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from transformers import TrainingArguments\n",
|
||
"\n",
|
||
"training_args = TrainingArguments(\n",
|
||
" output_dir=repo_name,\n",
|
||
" group_by_length=True,\n",
|
||
" per_device_train_batch_size=32,\n",
|
||
" gradient_accumulation_steps=1,\n",
|
||
" eval_accumulation_steps=1,\n",
|
||
" evaluation_strategy=\"steps\",\n",
|
||
" num_train_epochs=5,\n",
|
||
" gradient_checkpointing=True,\n",
|
||
" fp16=True,\n",
|
||
" save_steps=800,\n",
|
||
" eval_steps=800,\n",
|
||
" logging_steps=250,\n",
|
||
" learning_rate=1e-4,\n",
|
||
" warmup_steps=800,\n",
|
||
" save_total_limit=2,\n",
|
||
" report_to=\"tensorboard\"\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"id": "38cc611b",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/"
|
||
},
|
||
"id": "rY7vBmFCPFgC",
|
||
"outputId": "a180bf3f-f798-4947-ff58-207d7aaab695"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Using amp half precision backend\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from transformers import Trainer\n",
|
||
"\n",
|
||
"trainer = Trainer(\n",
|
||
" model=model,\n",
|
||
" data_collator=data_collator,\n",
|
||
" args=training_args,\n",
|
||
" compute_metrics=compute_metrics,\n",
|
||
" train_dataset=all,\n",
|
||
" eval_dataset=common_voice_test,\n",
|
||
" tokenizer=processor.feature_extractor,\n",
|
||
")"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"id": "ab7b22fa",
|
||
"metadata": {
|
||
"colab": {
|
||
"base_uri": "https://localhost:8080/",
|
||
"height": 312
|
||
},
|
||
"id": "9fRr9TG5pGBl",
|
||
"outputId": "8bdf1d11-bca1-46af-db67-518f85586f7a"
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"The following columns in the training set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length.\n",
|
||
"/workspace/.local/lib/python3.8/site-packages/transformers/optimization.py:306: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use thePyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
|
||
" warnings.warn(\n",
|
||
"***** Running training *****\n",
|
||
" Num examples = 159605\n",
|
||
" Num Epochs = 5\n",
|
||
" Instantaneous batch size per device = 32\n",
|
||
" Total train batch size (w. parallel, distributed & accumulation) = 32\n",
|
||
" Gradient Accumulation steps = 1\n",
|
||
" Total optimization steps = 24940\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"\n",
|
||
" <div>\n",
|
||
" \n",
|
||
" <progress value='24940' max='24940' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
|
||
" [24940/24940 14:54:01, Epoch 5/5]\n",
|
||
" </div>\n",
|
||
" <table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: left;\">\n",
|
||
" <th>Step</th>\n",
|
||
" <th>Training Loss</th>\n",
|
||
" <th>Validation Loss</th>\n",
|
||
" <th>Wer</th>\n",
|
||
" <th>Cer</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <td>800</td>\n",
|
||
" <td>3.420300</td>\n",
|
||
" <td>3.314820</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>1600</td>\n",
|
||
" <td>2.815100</td>\n",
|
||
" <td>0.850840</td>\n",
|
||
" <td>0.893788</td>\n",
|
||
" <td>0.234479</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>2400</td>\n",
|
||
" <td>0.941100</td>\n",
|
||
" <td>0.333538</td>\n",
|
||
" <td>0.372315</td>\n",
|
||
" <td>0.084735</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>3200</td>\n",
|
||
" <td>0.740800</td>\n",
|
||
" <td>0.257277</td>\n",
|
||
" <td>0.283963</td>\n",
|
||
" <td>0.064233</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>4000</td>\n",
|
||
" <td>0.651600</td>\n",
|
||
" <td>0.236474</td>\n",
|
||
" <td>0.258103</td>\n",
|
||
" <td>0.059464</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>4800</td>\n",
|
||
" <td>0.624200</td>\n",
|
||
" <td>0.203933</td>\n",
|
||
" <td>0.243332</td>\n",
|
||
" <td>0.054062</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>5600</td>\n",
|
||
" <td>0.575400</td>\n",
|
||
" <td>0.183210</td>\n",
|
||
" <td>0.215611</td>\n",
|
||
" <td>0.048234</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>6400</td>\n",
|
||
" <td>0.562600</td>\n",
|
||
" <td>0.182699</td>\n",
|
||
" <td>0.209116</td>\n",
|
||
" <td>0.046281</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>7200</td>\n",
|
||
" <td>0.534200</td>\n",
|
||
" <td>0.174398</td>\n",
|
||
" <td>0.203315</td>\n",
|
||
" <td>0.046776</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>8000</td>\n",
|
||
" <td>0.496500</td>\n",
|
||
" <td>0.170528</td>\n",
|
||
" <td>0.196285</td>\n",
|
||
" <td>0.044429</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>8800</td>\n",
|
||
" <td>0.504700</td>\n",
|
||
" <td>0.160374</td>\n",
|
||
" <td>0.188880</td>\n",
|
||
" <td>0.042167</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>9600</td>\n",
|
||
" <td>0.481400</td>\n",
|
||
" <td>0.160427</td>\n",
|
||
" <td>0.182742</td>\n",
|
||
" <td>0.041052</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>10400</td>\n",
|
||
" <td>0.447100</td>\n",
|
||
" <td>0.156585</td>\n",
|
||
" <td>0.182207</td>\n",
|
||
" <td>0.040592</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>11200</td>\n",
|
||
" <td>0.450900</td>\n",
|
||
" <td>0.161888</td>\n",
|
||
" <td>0.185296</td>\n",
|
||
" <td>0.043243</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>12000</td>\n",
|
||
" <td>0.441500</td>\n",
|
||
" <td>0.151254</td>\n",
|
||
" <td>0.176386</td>\n",
|
||
" <td>0.039725</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>12800</td>\n",
|
||
" <td>0.431300</td>\n",
|
||
" <td>0.151478</td>\n",
|
||
" <td>0.173930</td>\n",
|
||
" <td>0.039213</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>13600</td>\n",
|
||
" <td>0.416300</td>\n",
|
||
" <td>0.144519</td>\n",
|
||
" <td>0.169515</td>\n",
|
||
" <td>0.037672</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>14400</td>\n",
|
||
" <td>0.414200</td>\n",
|
||
" <td>0.147759</td>\n",
|
||
" <td>0.169871</td>\n",
|
||
" <td>0.038473</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>15200</td>\n",
|
||
" <td>0.418400</td>\n",
|
||
" <td>0.143047</td>\n",
|
||
" <td>0.166921</td>\n",
|
||
" <td>0.037583</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>16000</td>\n",
|
||
" <td>0.388600</td>\n",
|
||
" <td>0.143273</td>\n",
|
||
" <td>0.164426</td>\n",
|
||
" <td>0.037388</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>16800</td>\n",
|
||
" <td>0.379500</td>\n",
|
||
" <td>0.142606</td>\n",
|
||
" <td>0.164822</td>\n",
|
||
" <td>0.037258</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>17600</td>\n",
|
||
" <td>0.385900</td>\n",
|
||
" <td>0.135660</td>\n",
|
||
" <td>0.160446</td>\n",
|
||
" <td>0.036143</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>18400</td>\n",
|
||
" <td>0.376200</td>\n",
|
||
" <td>0.134396</td>\n",
|
||
" <td>0.155832</td>\n",
|
||
" <td>0.034930</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>19200</td>\n",
|
||
" <td>0.384000</td>\n",
|
||
" <td>0.137933</td>\n",
|
||
" <td>0.157595</td>\n",
|
||
" <td>0.035875</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>20000</td>\n",
|
||
" <td>0.376200</td>\n",
|
||
" <td>0.134363</td>\n",
|
||
" <td>0.153892</td>\n",
|
||
" <td>0.034552</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>20800</td>\n",
|
||
" <td>0.355900</td>\n",
|
||
" <td>0.133945</td>\n",
|
||
" <td>0.152526</td>\n",
|
||
" <td>0.035080</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>21600</td>\n",
|
||
" <td>0.368300</td>\n",
|
||
" <td>0.131489</td>\n",
|
||
" <td>0.151753</td>\n",
|
||
" <td>0.034226</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>22400</td>\n",
|
||
" <td>0.357200</td>\n",
|
||
" <td>0.130721</td>\n",
|
||
" <td>0.150664</td>\n",
|
||
" <td>0.034154</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>23200</td>\n",
|
||
" <td>0.349400</td>\n",
|
||
" <td>0.129449</td>\n",
|
||
" <td>0.149100</td>\n",
|
||
" <td>0.033476</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>24000</td>\n",
|
||
" <td>0.347600</td>\n",
|
||
" <td>0.128731</td>\n",
|
||
" <td>0.149120</td>\n",
|
||
" <td>0.033597</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <td>24800</td>\n",
|
||
" <td>0.347500</td>\n",
|
||
" <td>0.127098</td>\n",
|
||
" <td>0.147457</td>\n",
|
||
" <td>0.032896</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table><p>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-800\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-800/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-800/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-800/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-30400] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-1600\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-1600/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-1600/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-1600/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-31200] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-2400\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-2400/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-2400/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-2400/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-800] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-3200\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-3200/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-3200/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-3200/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-1600] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-4000\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-4000/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-4000/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-4000/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-2400] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-4800\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-4800/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-4800/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-4800/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-3200] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-5600\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-5600/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-5600/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-5600/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-4000] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-6400\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-6400/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-6400/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-6400/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-4800] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-7200\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-7200/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-7200/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-7200/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-5600] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-8000\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-8000/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-8000/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-8000/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-6400] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-8800\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-8800/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-8800/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-8800/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-7200] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-9600\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-9600/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-9600/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-9600/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-8000] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-10400\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-10400/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-10400/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-10400/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-8800] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-11200\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-11200/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-11200/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-11200/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-9600] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-12000\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-12000/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-12000/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-12000/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-10400] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-12800\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-12800/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-12800/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-12800/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-11200] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-13600\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-13600/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-13600/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-13600/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-12000] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-14400\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-14400/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-14400/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-14400/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-12800] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-15200\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-15200/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-15200/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-15200/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-13600] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-16000\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-16000/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-16000/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-16000/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-14400] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-16800\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-16800/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-16800/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-16800/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-15200] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-17600\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-17600/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-17600/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-17600/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-16000] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-18400\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-18400/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-18400/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-18400/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-16800] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-19200\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-19200/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-19200/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-19200/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-17600] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-20000\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-20000/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-20000/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-20000/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-18400] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-20800\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-20800/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-20800/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-20800/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-19200] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-21600\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-21600/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-21600/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-21600/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-20000] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-22400\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-22400/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-22400/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-22400/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-20800] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-23200\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-23200/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-23200/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-23200/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-21600] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-24000\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-24000/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-24000/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-24000/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-22400] due to args.save_total_limit\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 = 7267\n",
|
||
" Batch size = 8\n",
|
||
"Saving model checkpoint to wav2vec2-xls-r-300m-cs-250/checkpoint-24800\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-24800/config.json\n",
|
||
"Model weights saved in wav2vec2-xls-r-300m-cs-250/checkpoint-24800/pytorch_model.bin\n",
|
||
"Configuration saved in wav2vec2-xls-r-300m-cs-250/checkpoint-24800/preprocessor_config.json\n",
|
||
"Deleting older checkpoint [wav2vec2-xls-r-300m-cs-250/checkpoint-23200] due to args.save_total_limit\n",
|
||
"\n",
|
||
"\n",
|
||
"Training completed. Do not forget to share your model on huggingface.co/models =)\n",
|
||
"\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"TrainOutput(global_step=24940, training_loss=0.7262697845434511, metrics={'train_runtime': 53649.1292, 'train_samples_per_second': 14.875, 'train_steps_per_second': 0.465, 'total_flos': 1.1982083586402645e+20, 'train_loss': 0.7262697845434511, 'epoch': 5.0})"
|
||
]
|
||
},
|
||
"execution_count": 32,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"trainer.train()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"id": "6610bd0a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Dropping the following result as it does not have all the necessary fields:\n",
|
||
"{}\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"trainer.create_model_card()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"id": "ec5a5334",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Configuration saved in ./config.json\n",
|
||
"Model weights saved in ./pytorch_model.bin\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"model.save_pretrained('.')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "8d3d92c1",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.8.8"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|