James Briggs
commited on
Commit
•
c134b71
1
Parent(s):
ab0f88a
Added Graphcore/bert-base-uncased weights and configs
Browse files- README.md +74 -0
- all_results.json +8 -0
- config.json +26 -0
- ipu_config.json +27 -0
- pytorch_model.bin +3 -0
- 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_args.bin +3 -0
- 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-base-uncased
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results: []
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---
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# Graphcore/bert-base-uncased
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This model is a pre-trained BERT-Base 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 Base model trained on Wikipedia data.
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## Intended uses & limitations
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More information needed
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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 16 Graphcore Mk2 IPUs.
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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: 32
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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: 128
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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: 10500
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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: 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: 16384
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- total_eval_batch_size: 128
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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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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.0+cpu
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- Datasets 1.18.3.dev0
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- Tokenizers 0.10.3
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all_results.json
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{
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"epoch": 2.04,
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"train_loss": 1.7846279670726564,
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"train_runtime": 13858.2887,
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"train_samples": 16407928,
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"train_samples_per_second": 2409.431,
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"train_steps_per_second": 0.147
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}
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config.json
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{
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"_name_or_path": "./output-pretrain-bert-base-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": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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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": 12,
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"num_hidden_layers": 12,
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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.dev0",
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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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"executable_cache_dir": "./exe_cache",
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"gradient_accumulation_steps": 512,
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"inference_device_iterations": 4,
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"inference_replication_factor": 4,
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"ipus_per_replica": 4,
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"layers_per_ipu": [
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0,
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4,
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4,
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4
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],
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"matmul_proportion": 0.22,
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"optimizer_state_offchip": false,
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"optimum_version": "0.1.2",
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"output_mode": "final",
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"profile_dir": null,
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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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"seed": 42,
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"use_popdist": false
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:ab1d84f3c8581889214b56a524211492d4f8bb898dab0413d277f2981ac4ba93
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size 220405025
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer.json
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
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{"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-base-uncased", "tokenizer_class": "BertTokenizer"}
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train_results.json
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{
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"epoch": 2.04,
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"train_loss": 1.7846279670726564,
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"train_runtime": 13858.2887,
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"train_samples": 16407928,
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"train_samples_per_second": 2409.431,
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"train_steps_per_second": 0.147
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}
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trainer_state.json
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