metadata
tags:
- generated_from_trainer
datasets:
- wikitext
model-index:
- name: clm_output_medium
results: []
clm_output_medium
This model is a fine-tuned version of gpt2-medium on the wikitext-103-raw-v1 dataset. It achieves the following results on the evaluation set:
- Loss: 2.6973
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
wikitext-103-raw-v1 dataset
Training procedure
Trained on 16 Graphcore Mk2 IPUs using optimum-graphcore.
Command line:
python examples/language-modeling/run_clm.py \
--model_name_or_path gpt2-medium \
--ipu_config_name Graphcore/gpt2-medium-ipu \
--dataset_name wikitext \
--dataset_config_name wikitext-103-raw-v1 \
--do_train \
--do_eval \
--num_train_epochs 10 \
--dataloader_num_workers 64 \
--per_device_train_batch_size 1 \
--per_device_eval_batch_size 1 \
--gradient_accumulation_steps 256 \
--output_dir /tmp/clm_output_medium \
--logging_steps 5 \
--learning_rate 1e-5 \
--lr_scheduler_type linear \
--loss_scaling 16384 \
--weight_decay 0.01 \
--warmup_ratio 0.1 \
--ipu_config_overrides="embedding_serialization_factor=5,inference_device_iterations=9,replication_factor=2,inference_replication_factor=2,ipus_per_replica=8,layers_per_ipu=[0 3 3 3 3 4 4 4],matmul_proportion=0.25" \
--dataloader_drop_last \
--pod_type pod16
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 256
- total_train_batch_size: 1024
- total_eval_batch_size: 18
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- training precision: Mixed Precision
Training results
***** train metrics *****
"epoch": 10.0,
"train_loss": 2.8070910754504506,
"train_runtime": 11217.8167,
"train_samples": 114248,
"train_samples_per_second": 101.845,
"train_steps_per_second": 0.099
***** eval metrics *****
"eval_loss": 2.697265625,
"eval_samples": 240,
"perplexity": 14.83910053420958
Framework versions
- Transformers 4.18.0.dev0
- Pytorch 1.10.0+cpu
- Datasets 2.0.0
- Tokenizers 0.11.6