[s2s] Don't mention packed data in README (#6079)
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@@ -89,20 +89,20 @@ Then you can finetune mbart_cc25 on english-romanian with the following command.
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Best performing command:
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Best performing command:
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```bash
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```bash
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# optionally
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# optionally
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export ENRO_DIR='wmt_en_ro_packed_train_200' # Download instructions above
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export ENRO_DIR='wmt_en_ro' # Download instructions above
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# export WANDB_PROJECT="MT" # optional
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# export WANDB_PROJECT="MT" # optional
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export MAX_LEN=200
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export MAX_LEN=200
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export BS=4
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export BS=4
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export GAS=8 # gradient accumulation steps
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export GAS=8 # gradient accumulation steps
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./train_mbart_cc25_enro.sh --output_dir enro_finetune_baseline --label_smoothing 0.1 --fp16_opt_level=O1 --logger_name wandb --sortish_sampler
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./train_mbart_cc25_enro.sh --output_dir enro_finetune_baseline --label_smoothing 0.1 --fp16_opt_level=O1 --logger_name wandb --sortish_sampler
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```
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```
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This should take < 2h/epoch on a 16GB v100 and achieve val_avg_ BLEU score above 25. (you can see in wandb or metrics.json).
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This should take < 6h/epoch on a 16GB v100 and achieve val_avg_ BLEU score above 25. (you can see metrics in wandb or metrics.json).
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To get results in line with fairseq, you need to do some postprocessing.
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To get results in line with fairseq, you need to do some postprocessing.
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MultiGPU command
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MultiGPU command
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(using 8 GPUS as an example)
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(using 8 GPUS as an example)
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```bash
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```bash
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export ENRO_DIR='wmt_en_ro_packed_train_200' # Download instructions above
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export ENRO_DIR='wmt_en_ro' # Download instructions above
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# export WANDB_PROJECT="MT" # optional
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# export WANDB_PROJECT="MT" # optional
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export MAX_LEN=200
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export MAX_LEN=200
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export BS=4
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export BS=4
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