Commit
•
387585b
1
Parent(s):
b02bd0a
Update BERT large uncased checkpoint after running phase 1 (SL 128) and phase 2 (SL 512)
Browse files- README.md +141 -0
- all_results.json +8 -0
- config.json +7 -68
- ipu_config.json +32 -0
- pytorch_model.bin +2 -2
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- train_results.json +8 -0
- trainer_state.json +2467 -0
- training_state.pt → training_args.bin +2 -2
- vocab.txt +0 -0
README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- Graphcore/wikipedia-bert-128
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- Graphcore/wikipedia-bert-512
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model-index:
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- name: Graphcore/bert-large-uncased
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results: []
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---
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# Graphcore/bert-large-uncased
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This model is a pre-trained BERT-Large trained in two phases on the [Graphcore/wikipedia-bert-128](https://huggingface.co/datasets/Graphcore/wikipedia-bert-128) and [Graphcore/wikipedia-bert-512](https://huggingface.co/datasets/Graphcore/wikipedia-bert-512) datasets.
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## Model description
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Pre-trained BERT Large model trained on Wikipedia data.
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## Training and evaluation data
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Trained on wikipedia datasets:
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- [Graphcore/wikipedia-bert-128](https://huggingface.co/datasets/Graphcore/wikipedia-bert-128)
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- [Graphcore/wikipedia-bert-512](https://huggingface.co/datasets/Graphcore/wikipedia-bert-512)
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## Training procedure
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Trained MLM and NSP pre-training scheme from [Large Batch Optimization for Deep Learning: Training BERT in 76 minutes](https://arxiv.org/abs/1904.00962).
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Trained on 64 Graphcore Mk2 IPUs using [`optimum-graphcore`](https://github.com/huggingface/optimum-graphcore)
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Command lines:
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Phase 1:
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```
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python examples/language-modeling/run_pretraining.py \
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--config_name bert-large-uncased \
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--tokenizer_name bert-large-uncased \
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--ipu_config_name Graphcore/bert-large-ipu \
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--dataset_name Graphcore/wikipedia-bert-128 \
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--do_train \
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--logging_steps 5 \
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--max_seq_length 128 \
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--max_steps 10550 \
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--is_already_preprocessed \
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--dataloader_num_workers 64 \
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--dataloader_mode async_rebatched \
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--lamb \
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--lamb_no_bias_correction \
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| 50 |
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--per_device_train_batch_size 8 \
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| 51 |
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--gradient_accumulation_steps 512 \
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--pod_type pod64 \
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--learning_rate 0.006 \
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--lr_scheduler_type linear \
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--loss_scaling 32768 \
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--weight_decay 0.01 \
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| 57 |
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--warmup_ratio 0.28 \
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--config_overrides "layer_norm_eps=0.001" \
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| 59 |
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--ipu_config_overrides "matmul_proportion=[0.14 0.19 0.19 0.19]" \
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--output_dir output-pretrain-bert-large-phase1
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```
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Phase 2:
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```
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python examples/language-modeling/run_pretraining.py \
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--config_name bert-large-uncased \
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| 67 |
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--tokenizer_name bert-large-uncased \
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--model_name_or_path ./output-pretrain-bert-large-phase1 \
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--ipu_config_name Graphcore/bert-large-ipu \
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--dataset_name Graphcore/wikipedia-bert-512 \
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--do_train \
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--logging_steps 5 \
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--max_seq_length 512 \
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--max_steps 2038 \
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--is_already_preprocessed \
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--dataloader_num_workers 96 \
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--dataloader_mode async_rebatched \
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--lamb \
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--lamb_no_bias_correction \
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--per_device_train_batch_size 2 \
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--gradient_accumulation_steps 512 \
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--pod_type pod64 \
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--learning_rate 0.002828 \
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--lr_scheduler_type linear \
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--loss_scaling 16384 \
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--weight_decay 0.01 \
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--warmup_ratio 0.128 \
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--config_overrides "layer_norm_eps=0.001" \
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--ipu_config_overrides "matmul_proportion=[0.14 0.19 0.19 0.19]" \
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--output_dir output-pretrain-bert-large-phase2
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```
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### Training hyperparameters
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The following hyperparameters were used during phase 1 training:
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- learning_rate: 0.006
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: IPU
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- gradient_accumulation_steps: 512
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- total_train_batch_size: 65536
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- total_eval_batch_size: 512
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- optimizer: LAMB
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.28
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- training_steps: 10550
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- training precision: Mixed Precision
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The following hyperparameters were used during phase 2 training:
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- learning_rate: 0.002828
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: IPU
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- gradient_accumulation_steps: 512
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- total_train_batch_size: 16384
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| 118 |
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- total_eval_batch_size: 512
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- optimizer: LAMB
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.128
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- training_steps: 2038
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- training precision: Mixed Precision
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### Training results
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```
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train/epoch: 2.04
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train/global_step: 2038
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train/loss: 1.2002
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train/train_runtime: 12022.3897
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train/train_steps_per_second: 0.17
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train/train_samples_per_second: 2777.367
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```
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.10.0+cpu
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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all_results.json
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{
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"epoch": 2.04,
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"train_loss": 0.02294661615032911,
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| 4 |
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"train_runtime": 3034.1773,
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| 5 |
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"train_samples": 16407928,
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| 6 |
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"train_samples_per_second": 11004.826,
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"train_steps_per_second": 0.672
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}
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config.json
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{
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"_name_or_path": "
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"architectures": [
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"
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],
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"
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"
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"auto_loss_scaling": false,
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"batch_size": 2,
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"batches_per_step": 1,
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"checkpoint_output_dir": "/localdata/jamesbr/dev/pretrained_checkpoints/pytorch_bert_large_phase2",
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"checkpoint_steps": null,
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"compile_only": false,
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"config": null,
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"custom_ops": true,
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"dataloader_workers": 64,
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"dataset": "pretraining",
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"disable_progress_bar": true,
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"embedding_serialization_factor": 2,
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"enable_half_first_order_momentum": false,
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"enable_half_partials": true,
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"executable_cache_dir": "",
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"file_buffer_size": 10,
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"global_batch_size": 16384,
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"gradient_accumulation": 2048,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"input_files": [
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"data/wikipedia/384/*.tfrecord"
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],
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"intermediate_size": 4096,
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| 35 |
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"ipus_per_replica": 4,
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"layer_norm_eps": 0.001,
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"layers_per_ipu": [
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3,
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7,
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7,
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7
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],
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"learning_rate": 0.002828,
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"loss_scaling": 8192.0,
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"lr_schedule": "linear",
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"lr_warmup": 0.128,
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"mask_tokens": 56,
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"matmul_proportion": [
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0.15,
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0.25,
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0.25,
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0.25
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],
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 16,
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"num_epochs": null,
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"num_hidden_layers": 24,
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"optimizer": "LAMB",
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"optimizer_state_offchip": true,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"
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"
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"profile": false,
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"profile_dir": "profile",
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"random_seed": 42,
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"recompute_checkpoint_every_layer": true,
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"replicated_tensor_sharding": true,
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"replication_factor": 4,
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"restore_steps_and_optimizer": false,
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"samples_per_step": 16384,
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"sdk_version": "poplar_sdk-ubuntu_18_04-2.3.0-EA.1+716-757737e247",
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"sequence_length": 384,
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"squad_do_training": true,
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"squad_do_validation": true,
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"synthetic_data": false,
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"training_steps": 2137,
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"transformers_version": "4.7.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"
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"vocab_size": 30522,
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"wandb": true,
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"wandb_param_steps": null,
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"weight_decay": 0.01
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}
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{
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"_name_or_path": "./output-pretrain-bert-large-phase1",
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"architectures": [
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"PoptorchPipelinedBertForPreTraining"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 0.001,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 16,
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"num_hidden_layers": 24,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float16",
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"transformers_version": "4.17.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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ipu_config.json
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{
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"device_iterations": 1,
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"embedding_serialization_factor": 2,
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"enable_half_first_order_momentum": true,
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"enable_half_partials": true,
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| 6 |
+
"executable_cache_dir": "./exe_cache",
|
| 7 |
+
"gradient_accumulation_steps": 512,
|
| 8 |
+
"inference_device_iterations": 4,
|
| 9 |
+
"inference_replication_factor": 16,
|
| 10 |
+
"ipus_per_replica": 4,
|
| 11 |
+
"layers_per_ipu": [
|
| 12 |
+
3,
|
| 13 |
+
7,
|
| 14 |
+
7,
|
| 15 |
+
7
|
| 16 |
+
],
|
| 17 |
+
"matmul_proportion": [
|
| 18 |
+
0.1,
|
| 19 |
+
0.15,
|
| 20 |
+
0.15,
|
| 21 |
+
0.15
|
| 22 |
+
],
|
| 23 |
+
"optimizer_state_offchip": true,
|
| 24 |
+
"optimum_version": "1.0.0",
|
| 25 |
+
"output_mode": "final",
|
| 26 |
+
"profile_dir": "",
|
| 27 |
+
"recompute_checkpoint_every_layer": true,
|
| 28 |
+
"replicated_tensor_sharding": true,
|
| 29 |
+
"replication_factor": 16,
|
| 30 |
+
"seed": 42,
|
| 31 |
+
"use_popdist": false
|
| 32 |
+
}
|
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:15c5db5802c5caced9e33d4bffcdec6a7616973bb7c477788ad7a595dd77f8c8
|
| 3 |
+
size 672706657
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "bert-large-uncased", "tokenizer_class": "BertTokenizer"}
|
train_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 2.04,
|
| 3 |
+
"train_loss": 0.02294661615032911,
|
| 4 |
+
"train_runtime": 3034.1773,
|
| 5 |
+
"train_samples": 16407928,
|
| 6 |
+
"train_samples_per_second": 11004.826,
|
| 7 |
+
"train_steps_per_second": 0.672
|
| 8 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,2467 @@
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|
|
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|
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training_state.pt → training_args.bin
RENAMED
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@@ -1,3 +1,3 @@
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vocab.txt
ADDED
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