!pip install simpletransformers
Collecting simpletransformers
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Collecting transformers>=3.0.2
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[?25hCollecting streamlit
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[?25hCollecting seqeval
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Collecting tqdm>=4.47.0
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Collecting wandb
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[?25hCollecting tokenizers
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[?25hCollecting tensorboardx
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Collecting sentencepiece!=0.1.92
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Collecting sacremoses
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Collecting pydeck>=0.1.dev5
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Collecting watchdog
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Collecting validators
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Collecting blinker
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Collecting gql==0.2.0
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Collecting configparser>=3.8.1
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Collecting ipykernel>=5.1.2; python_version >= "3.4"
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Collecting graphql-core<2,>=0.5.0
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Building wheels for collected packages: seqeval, sacremoses, watchdog, blinker, gql, subprocess32, pathtools, graphql-core
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Stored in directory: /root/.cache/pip/wheels/92/a0/00/8690a57883956a301d91cf4ec999cc0b258b01e3f548f86e89
Building wheel for gql (setup.py) ... [?25l[?25hdone
Created wheel for gql: filename=gql-0.2.0-cp36-none-any.whl size=7630 sha256=0296d94cc81bbf8601c1ce3281ad60c61917b53a08f5cedd736dbd8fd28a0945
Stored in directory: /root/.cache/pip/wheels/ce/0e/7b/58a8a5268655b3ad74feef5aa97946f0addafb3cbb6bd2da23
Building wheel for subprocess32 (setup.py) ... [?25l[?25hdone
Created wheel for subprocess32: filename=subprocess32-3.5.4-cp36-none-any.whl size=6489 sha256=17c9493efecdcf44c19bfbb395d66820a88d6204eb60de33deac1708662f649f
Stored in directory: /root/.cache/pip/wheels/68/39/1a/5e402bdfdf004af1786c8b853fd92f8c4a04f22aad179654d1
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Building wheel for graphql-core (setup.py) ... [?25l[?25hdone
Created wheel for graphql-core: filename=graphql_core-1.1-cp36-none-any.whl size=104650 sha256=76facbd1af6b52ad86e249b6d07ee3f3a23be3abdd2ed115514c986c37931033
Stored in directory: /root/.cache/pip/wheels/45/99/d7/c424029bb0fe910c63b68dbf2aa20d3283d023042521bcd7d5
Successfully built seqeval sacremoses watchdog blinker gql subprocess32 pathtools graphql-core
[31mERROR: google-colab 1.0.0 has requirement ipykernel~=4.10, but you'll have ipykernel 5.3.4 which is incompatible.[0m
[31mERROR: transformers 3.0.2 has requirement tokenizers==0.8.1.rc1, but you'll have tokenizers 0.8.1 which is incompatible.[0m
Installing collected packages: sentencepiece, tokenizers, tqdm, sacremoses, transformers, base58, enum-compat, ipykernel, pydeck, pathtools, watchdog, validators, blinker, streamlit, seqeval, graphql-core, gql, smmap, gitdb, GitPython, docker-pycreds, configparser, shortuuid, sentry-sdk, subprocess32, wandb, tensorboardx, simpletransformers
Found existing installation: tqdm 4.41.1
Uninstalling tqdm-4.41.1:
Successfully uninstalled tqdm-4.41.1
Found existing installation: ipykernel 4.10.1
Uninstalling ipykernel-4.10.1:
Successfully uninstalled ipykernel-4.10.1
Successfully installed GitPython-3.1.7 base58-2.0.1 blinker-1.4 configparser-5.0.0 docker-pycreds-0.4.0 enum-compat-0.0.3 gitdb-4.0.5 gql-0.2.0 graphql-core-1.1 ipykernel-5.3.4 pathtools-0.1.2 pydeck-0.5.0b1 sacremoses-0.0.43 sentencepiece-0.1.91 sentry-sdk-0.16.5 seqeval-0.0.12 shortuuid-1.0.1 simpletransformers-0.47.3 smmap-3.0.4 streamlit-0.65.2 subprocess32-3.5.4 tensorboardx-2.1 tokenizers-0.8.1 tqdm-4.48.2 transformers-3.0.2 validators-0.18.0 wandb-0.9.5 watchdog-0.10.3
!wget https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-v1.zip
--2020-08-24 15:02:27-- https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-v1.zip
Resolving s3.amazonaws.com (s3.amazonaws.com)... 52.216.80.139
Connecting to s3.amazonaws.com (s3.amazonaws.com)|52.216.80.139|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 4475746 (4.3M) [application/zip]
Saving to: ‘wikitext-2-v1.zip’
wikitext-2-v1.zip 100%[===================>] 4.27M 2.93MB/s in 1.5s
2020-08-24 15:02:29 (2.93 MB/s) - ‘wikitext-2-v1.zip’ saved [4475746/4475746]
!unzip wikitext-2-v1.zip
Archive: wikitext-2-v1.zip
creating: wikitext-2/
inflating: wikitext-2/wiki.test.tokens
inflating: wikitext-2/wiki.valid.tokens
inflating: wikitext-2/wiki.train.tokens
ls wikitext-2/
wiki.test.tokens wiki.train.tokens wiki.valid.tokens
from simpletransformers.language_modeling import LanguageModelingModel
import logging
logging.basicConfig(level=logging.INFO)
transformers_logger = logging.getLogger("transformers")
transformers_logger.setLevel(logging.WARNING)
train_args = {
"reprocess_input_data": True,
"overwrite_output_dir": True,
}
model = LanguageModelingModel('bert', 'bert-base-cased', args=train_args, use_cuda=True)
[34m[1mwandb[0m: [33mWARNING[0m W&B installed but not logged in. Run `wandb login` or set the WANDB_API_KEY env variable.
INFO:filelock:Lock 139946366819016 acquired on cache_dir/5e8a2b4893d13790ed4150ca1906be5f7a03d6c4ddf62296c383f6db42814db2.e13dbb970cb325137104fb2e5f36fe865f27746c6b526f6352861b1980eb80b1.lock
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INFO:filelock:Lock 139948275897176 acquired on cache_dir/b945b69218e98b3e2c95acf911789741307dec43c698d35fad11c1ae28bda352.9da767be51e1327499df13488672789394e2ca38b877837e52618a67d7002391.lock
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INFO:filelock:Lock 139948275897176 released on cache_dir/b945b69218e98b3e2c95acf911789741307dec43c698d35fad11c1ae28bda352.9da767be51e1327499df13488672789394e2ca38b877837e52618a67d7002391.lock
INFO:filelock:Lock 139947842575384 acquired on cache_dir/d8f11f061e407be64c4d5d7867ee61d1465263e24085cfa26abf183fdc830569.3fadbea36527ae472139fe84cddaa65454d7429f12d543d80bfc3ad70de55ac2.lock
HBox(children=(FloatProgress(value=0.0, description='Downloading', max=435779157.0, style=ProgressStyle(descri…
INFO:filelock:Lock 139947842575384 released on cache_dir/d8f11f061e407be64c4d5d7867ee61d1465263e24085cfa26abf183fdc830569.3fadbea36527ae472139fe84cddaa65454d7429f12d543d80bfc3ad70de55ac2.lock
WARNING:transformers.modeling_utils:Some weights of the model checkpoint at bert-base-cased were not used when initializing BertForMaskedLM: ['cls.seq_relationship.weight', 'cls.seq_relationship.bias']
- This IS expected if you are initializing BertForMaskedLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPretraining model).
- This IS NOT expected if you are initializing BertForMaskedLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
WARNING:transformers.modeling_utils:Some weights of BertForMaskedLM were not initialized from the model checkpoint at bert-base-cased and are newly initialized: ['cls.predictions.decoder.bias']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
model.train_model("wikitext-2/wiki.train.tokens", eval_file="wikitext-2/wiki.test.tokens", batch_size=32)
INFO:simpletransformers.language_modeling.language_modeling_utils: Creating features from dataset file at cache_dir/
HBox(children=(FloatProgress(value=0.0, max=23767.0), HTML(value='')))
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (724 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (629 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (520 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (910 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (517 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (511 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (616 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (538 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (848 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (518 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (515 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (513 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (533 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (663 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (520 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (640 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (538 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (579 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (519 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (527 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (839 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (547 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (524 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (589 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (546 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (519 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (552 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (535 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (522 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (536 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (524 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (546 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (666 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (807 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (522 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (585 > 512). Running this sequence through the model will result in indexing errors
WARNING:transformers.tokenization_utils_base:Token indices sequence length is longer than the specified maximum sequence length for this model (682 > 512). Running this sequence through the model will result in indexing errors
HBox(children=(FloatProgress(value=0.0, max=19808.0), HTML(value='')))
INFO:simpletransformers.language_modeling.language_modeling_utils: Saving features into cached file cache_dir/bert_cached_lm_126_wiki.train.tokens
INFO:simpletransformers.language_modeling.language_modeling_model: Training started
HBox(children=(FloatProgress(value=0.0, description='Epoch', max=1.0, style=ProgressStyle(description_width='i…
HBox(children=(FloatProgress(value=0.0, description='Running Epoch 0 of 1', max=2476.0, style=ProgressStyle(de…
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-6-6f25e41f04f9> in <module>()
----> 1 model.train_model("wikitext-2/wiki.train.tokens", eval_file="wikitext-2/wiki.test.tokens", batch_size=32)
/usr/local/lib/python3.6/dist-packages/simpletransformers/language_modeling/language_modeling_model.py in train_model(self, train_file, output_dir, show_running_loss, args, eval_file, verbose, **kwargs)
368 eval_file=eval_file,
369 verbose=verbose,
--> 370 **kwargs,
371 )
372
/usr/local/lib/python3.6/dist-packages/simpletransformers/language_modeling/language_modeling_model.py in train(self, train_dataset, output_dir, show_running_loss, eval_file, verbose, **kwargs)
564 if args.fp16:
565 with amp.autocast():
--> 566 outputs = model(**inputs)
567 # model outputs are always tuple in pytorch-transformers (see doc)
568 loss = outputs[0]
TypeError: BertForMaskedLM object argument after ** must be a mapping, not Tensor