[s2s README] Add more dataset download instructions #6737
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## master #6737 +/- ##
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- Coverage 80.02% 79.92% -0.11%
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sshleifer
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* Only access loss tensor every logging_steps * tensor.item() was being called every step. This must not be done for XLA:TPU tensors as it's terrible for performance causing TPU<>CPU communication at each step. On RoBERTa MLM for example, it reduces step time by 30%, should be larger for smaller step time models/tasks. * Train batch size was not correct in case a user uses the `per_gpu_train_batch_size` flag * Avg reduce loss accross eval shards * Fix style (#6803) * t5 model should make decoder_attention_mask (#6800) * [s2s] Test hub configs in self-scheduled CI (#6809) * [s2s] round runtime in run_eval (#6798) * Pegasus finetune script: add --adafactor (#6811) * [bart] rename self-attention -> attention (#6708) * [tests] fix typos in inputs (#6818) * Fixed open in colab link (#6825) * Add model card for singbert lite. Update widget for singbert and singbert-large. (#6827) * BR_BERTo model card (#6793) * clearly indicate shuffle=False (#6312) * Clarify shuffle * clarify shuffle Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> * [s2s README] Add more dataset download instructions (#6737) * Style * Patch logging issue * Set default logging level to `WARNING` instead of `INFO` * TF Flaubert w/ pre-norm (#6841) * Dataset and DataCollator for BERT Next Sentence Prediction (NSP) task (#6644) * add datacollator and dataset for next sentence prediction task * bug fix (numbers of special tokens & truncate sequences) * bug fix (+ dict inputs support for data collator) * add padding for nsp data collator; renamed cached files to avoid conflict. * add test for nsp data collator * Style Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr> * Fix in Adafactor docstrings (#6845) * Fix resuming training for Windows (#6847) * Only access loss tensor every logging_steps * tensor.item() was being called every step. This must not be done for XLA:TPU tensors as it's terrible for performance causing TPU<>CPU communication at each step. On RoBERTa MLM for example, it reduces step time by 30%, should be larger for smaller step time models/tasks. * Train batch size was not correct in case a user uses the `per_gpu_train_batch_size` flag * Avg reduce loss accross eval shards * comments Co-authored-by: Sam Shleifer <sshleifer@gmail.com> Co-authored-by: Stas Bekman <stas00@users.noreply.github.com> Co-authored-by: Thomas Ashish Cherian <6967017+PandaWhoCodes@users.noreply.github.com> Co-authored-by: Zane Lim <zyuanlim@gmail.com> Co-authored-by: Rodolfo De Nadai <rdenadai@gmail.com> Co-authored-by: xujiaze13 <37360975+xujiaze13@users.noreply.github.com> Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr> Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Huang Lianzhe <hlz@pku.edu.cn> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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* Only access loss tensor every logging_steps * tensor.item() was being called every step. This must not be done for XLA:TPU tensors as it's terrible for performance causing TPU<>CPU communication at each step. On RoBERTa MLM for example, it reduces step time by 30%, should be larger for smaller step time models/tasks. * Train batch size was not correct in case a user uses the `per_gpu_train_batch_size` flag * Avg reduce loss accross eval shards * Fix style (huggingface#6803) * t5 model should make decoder_attention_mask (huggingface#6800) * [s2s] Test hub configs in self-scheduled CI (huggingface#6809) * [s2s] round runtime in run_eval (huggingface#6798) * Pegasus finetune script: add --adafactor (huggingface#6811) * [bart] rename self-attention -> attention (huggingface#6708) * [tests] fix typos in inputs (huggingface#6818) * Fixed open in colab link (huggingface#6825) * Add model card for singbert lite. Update widget for singbert and singbert-large. (huggingface#6827) * BR_BERTo model card (huggingface#6793) * clearly indicate shuffle=False (huggingface#6312) * Clarify shuffle * clarify shuffle Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> * [s2s README] Add more dataset download instructions (huggingface#6737) * Style * Patch logging issue * Set default logging level to `WARNING` instead of `INFO` * TF Flaubert w/ pre-norm (huggingface#6841) * Dataset and DataCollator for BERT Next Sentence Prediction (NSP) task (huggingface#6644) * add datacollator and dataset for next sentence prediction task * bug fix (numbers of special tokens & truncate sequences) * bug fix (+ dict inputs support for data collator) * add padding for nsp data collator; renamed cached files to avoid conflict. * add test for nsp data collator * Style Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr> * Fix in Adafactor docstrings (huggingface#6845) * Fix resuming training for Windows (huggingface#6847) * Only access loss tensor every logging_steps * tensor.item() was being called every step. This must not be done for XLA:TPU tensors as it's terrible for performance causing TPU<>CPU communication at each step. On RoBERTa MLM for example, it reduces step time by 30%, should be larger for smaller step time models/tasks. * Train batch size was not correct in case a user uses the `per_gpu_train_batch_size` flag * Avg reduce loss accross eval shards * comments Co-authored-by: Sam Shleifer <sshleifer@gmail.com> Co-authored-by: Stas Bekman <stas00@users.noreply.github.com> Co-authored-by: Thomas Ashish Cherian <6967017+PandaWhoCodes@users.noreply.github.com> Co-authored-by: Zane Lim <zyuanlim@gmail.com> Co-authored-by: Rodolfo De Nadai <rdenadai@gmail.com> Co-authored-by: xujiaze13 <37360975+xujiaze13@users.noreply.github.com> Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr> Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Huang Lianzhe <hlz@pku.edu.cn> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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* Only access loss tensor every logging_steps * tensor.item() was being called every step. This must not be done for XLA:TPU tensors as it's terrible for performance causing TPU<>CPU communication at each step. On RoBERTa MLM for example, it reduces step time by 30%, should be larger for smaller step time models/tasks. * Train batch size was not correct in case a user uses the `per_gpu_train_batch_size` flag * Avg reduce loss accross eval shards * Fix style (huggingface#6803) * t5 model should make decoder_attention_mask (huggingface#6800) * [s2s] Test hub configs in self-scheduled CI (huggingface#6809) * [s2s] round runtime in run_eval (huggingface#6798) * Pegasus finetune script: add --adafactor (huggingface#6811) * [bart] rename self-attention -> attention (huggingface#6708) * [tests] fix typos in inputs (huggingface#6818) * Fixed open in colab link (huggingface#6825) * Add model card for singbert lite. Update widget for singbert and singbert-large. (huggingface#6827) * BR_BERTo model card (huggingface#6793) * clearly indicate shuffle=False (huggingface#6312) * Clarify shuffle * clarify shuffle Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> * [s2s README] Add more dataset download instructions (huggingface#6737) * Style * Patch logging issue * Set default logging level to `WARNING` instead of `INFO` * TF Flaubert w/ pre-norm (huggingface#6841) * Dataset and DataCollator for BERT Next Sentence Prediction (NSP) task (huggingface#6644) * add datacollator and dataset for next sentence prediction task * bug fix (numbers of special tokens & truncate sequences) * bug fix (+ dict inputs support for data collator) * add padding for nsp data collator; renamed cached files to avoid conflict. * add test for nsp data collator * Style Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr> * Fix in Adafactor docstrings (huggingface#6845) * Fix resuming training for Windows (huggingface#6847) * Only access loss tensor every logging_steps * tensor.item() was being called every step. This must not be done for XLA:TPU tensors as it's terrible for performance causing TPU<>CPU communication at each step. On RoBERTa MLM for example, it reduces step time by 30%, should be larger for smaller step time models/tasks. * Train batch size was not correct in case a user uses the `per_gpu_train_batch_size` flag * Avg reduce loss accross eval shards * comments Co-authored-by: Sam Shleifer <sshleifer@gmail.com> Co-authored-by: Stas Bekman <stas00@users.noreply.github.com> Co-authored-by: Thomas Ashish Cherian <6967017+PandaWhoCodes@users.noreply.github.com> Co-authored-by: Zane Lim <zyuanlim@gmail.com> Co-authored-by: Rodolfo De Nadai <rdenadai@gmail.com> Co-authored-by: xujiaze13 <37360975+xujiaze13@users.noreply.github.com> Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr> Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Huang Lianzhe <hlz@pku.edu.cn> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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* Only access loss tensor every logging_steps * tensor.item() was being called every step. This must not be done for XLA:TPU tensors as it's terrible for performance causing TPU<>CPU communication at each step. On RoBERTa MLM for example, it reduces step time by 30%, should be larger for smaller step time models/tasks. * Train batch size was not correct in case a user uses the `per_gpu_train_batch_size` flag * Avg reduce loss accross eval shards * Fix style (huggingface#6803) * t5 model should make decoder_attention_mask (huggingface#6800) * [s2s] Test hub configs in self-scheduled CI (huggingface#6809) * [s2s] round runtime in run_eval (huggingface#6798) * Pegasus finetune script: add --adafactor (huggingface#6811) * [bart] rename self-attention -> attention (huggingface#6708) * [tests] fix typos in inputs (huggingface#6818) * Fixed open in colab link (huggingface#6825) * Add model card for singbert lite. Update widget for singbert and singbert-large. (huggingface#6827) * BR_BERTo model card (huggingface#6793) * clearly indicate shuffle=False (huggingface#6312) * Clarify shuffle * clarify shuffle Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> * [s2s README] Add more dataset download instructions (huggingface#6737) * Style * Patch logging issue * Set default logging level to `WARNING` instead of `INFO` * TF Flaubert w/ pre-norm (huggingface#6841) * Dataset and DataCollator for BERT Next Sentence Prediction (NSP) task (huggingface#6644) * add datacollator and dataset for next sentence prediction task * bug fix (numbers of special tokens & truncate sequences) * bug fix (+ dict inputs support for data collator) * add padding for nsp data collator; renamed cached files to avoid conflict. * add test for nsp data collator * Style Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr> * Fix in Adafactor docstrings (huggingface#6845) * Fix resuming training for Windows (huggingface#6847) * Only access loss tensor every logging_steps * tensor.item() was being called every step. This must not be done for XLA:TPU tensors as it's terrible for performance causing TPU<>CPU communication at each step. On RoBERTa MLM for example, it reduces step time by 30%, should be larger for smaller step time models/tasks. * Train batch size was not correct in case a user uses the `per_gpu_train_batch_size` flag * Avg reduce loss accross eval shards * comments Co-authored-by: Sam Shleifer <sshleifer@gmail.com> Co-authored-by: Stas Bekman <stas00@users.noreply.github.com> Co-authored-by: Thomas Ashish Cherian <6967017+PandaWhoCodes@users.noreply.github.com> Co-authored-by: Zane Lim <zyuanlim@gmail.com> Co-authored-by: Rodolfo De Nadai <rdenadai@gmail.com> Co-authored-by: xujiaze13 <37360975+xujiaze13@users.noreply.github.com> Co-authored-by: Kevin Canwen Xu <canwenxu@126.com> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr> Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Huang Lianzhe <hlz@pku.edu.cn> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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Improves formatting in seq2seq readme and adds download instructions for wmt-en-de and cnn_dm_v2 (cleaned cnn_dm without empty examples).