uer commited on
Commit
934000d
1 Parent(s): 045a312

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +6 -6
README.md CHANGED
@@ -115,7 +115,7 @@ python3 preprocess.py --corpus_path corpora/cluecorpussmall.txt \
115
  --vocab_path models/google_zh_vocab.txt \
116
  --dataset_path cluecorpussmall_seq128_dataset.pt \
117
  --processes_num 32 --seq_length 128 \
118
- --dynamic_masking --target mlm
119
  ```
120
 
121
  ```
@@ -126,7 +126,7 @@ python3 pretrain.py --dataset_path cluecorpussmall_seq128_dataset.pt \
126
  --world_size 8 --gpu_ranks 0 1 2 3 4 5 6 7 \
127
  --total_steps 1000000 --save_checkpoint_steps 100000 --report_steps 50000 \
128
  --learning_rate 1e-4 --batch_size 64 \
129
- --embedding word_pos_seg --encoder transformer --mask fully_visible --target mlm --tie_weights
130
  ```
131
 
132
  Stage2:
@@ -136,19 +136,19 @@ python3 preprocess.py --corpus_path corpora/cluecorpussmall.txt \
136
  --vocab_path models/google_zh_vocab.txt \
137
  --dataset_path cluecorpussmall_seq512_dataset.pt \
138
  --processes_num 32 --seq_length 512 \
139
- --dynamic_masking --target mlm
140
  ```
141
 
142
  ```
143
  python3 pretrain.py --dataset_path cluecorpussmall_seq512_dataset.pt \
144
- --pretrained_model_path models/cluecorpussmall_roberta_medium_seq128_model.bin-1000000 \
145
  --vocab_path models/google_zh_vocab.txt \
 
146
  --config_path models/bert/medium_config.json \
147
  --output_model_path models/cluecorpussmall_roberta_medium_seq512_model.bin \
148
  --world_size 8 --gpu_ranks 0 1 2 3 4 5 6 7 \
149
  --total_steps 250000 --save_checkpoint_steps 50000 --report_steps 10000 \
150
  --learning_rate 5e-5 --batch_size 16 \
151
- --embedding word_pos_seg --encoder transformer --mask fully_visible --target mlm --tie_weights
152
  ```
153
 
154
  Finally, we convert the pre-trained model into Huggingface's format:
@@ -156,7 +156,7 @@ Finally, we convert the pre-trained model into Huggingface's format:
156
  ```
157
  python3 scripts/convert_bert_from_uer_to_huggingface.py --input_model_path models/cluecorpussmall_roberta_medium_seq512_model.bin-250000 \
158
  --output_model_path pytorch_model.bin \
159
- --layers_num 8 --target mlm
160
  ```
161
 
162
  ### BibTeX entry and citation info
 
115
  --vocab_path models/google_zh_vocab.txt \
116
  --dataset_path cluecorpussmall_seq128_dataset.pt \
117
  --processes_num 32 --seq_length 128 \
118
+ --dynamic_masking --data_processor mlm
119
  ```
120
 
121
  ```
 
126
  --world_size 8 --gpu_ranks 0 1 2 3 4 5 6 7 \
127
  --total_steps 1000000 --save_checkpoint_steps 100000 --report_steps 50000 \
128
  --learning_rate 1e-4 --batch_size 64 \
129
+ --data_processor mlm --target mlm
130
  ```
131
 
132
  Stage2:
 
136
  --vocab_path models/google_zh_vocab.txt \
137
  --dataset_path cluecorpussmall_seq512_dataset.pt \
138
  --processes_num 32 --seq_length 512 \
139
+ --dynamic_masking --data_processor mlm
140
  ```
141
 
142
  ```
143
  python3 pretrain.py --dataset_path cluecorpussmall_seq512_dataset.pt \
 
144
  --vocab_path models/google_zh_vocab.txt \
145
+ --pretrained_model_path models/cluecorpussmall_roberta_medium_seq128_model.bin-1000000 \
146
  --config_path models/bert/medium_config.json \
147
  --output_model_path models/cluecorpussmall_roberta_medium_seq512_model.bin \
148
  --world_size 8 --gpu_ranks 0 1 2 3 4 5 6 7 \
149
  --total_steps 250000 --save_checkpoint_steps 50000 --report_steps 10000 \
150
  --learning_rate 5e-5 --batch_size 16 \
151
+ --data_processor mlm --target mlm
152
  ```
153
 
154
  Finally, we convert the pre-trained model into Huggingface's format:
 
156
  ```
157
  python3 scripts/convert_bert_from_uer_to_huggingface.py --input_model_path models/cluecorpussmall_roberta_medium_seq512_model.bin-250000 \
158
  --output_model_path pytorch_model.bin \
159
+ --layers_num 8 --type mlm
160
  ```
161
 
162
  ### BibTeX entry and citation info