93 lines
2.0 KiB
Markdown
93 lines
2.0 KiB
Markdown
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---
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library_name: transformers
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tags:
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- generated_from_trainer
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datasets:
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- wikitext
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metrics:
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- accuracy
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model-index:
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- name: gpt2-verification
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results:
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- task:
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name: Causal Language Modeling
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type: text-generation
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dataset:
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name: wikitext wikitext-2-raw-v1
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type: wikitext
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args: wikitext-2-raw-v1
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.18546350602802217
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# gpt2-verification
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This model utilizes the GPT2 architecture and GPT2 tokenizer, and was trained from scratch using wikitext-2-raw-v1.
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It achieves the following results on the evaluation set:
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- Loss: 6.0571
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- Accuracy: 0.1855
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## Model Train Command
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```
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CUDA_VISIBLE_DEVICES=0 uv run python examples/pytorch/language-modeling/run_clm.py \
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--model_type gpt2 \
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--tokenizer_name gpt2 \
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--dataset_name wikitext \
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--dataset_config_name wikitext-2-raw-v1 \
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--per_device_train_batch_size 2 \
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--per_device_eval_batch_size 2 \
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--num_train_epochs 3 \
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--do_train \
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--do_eval \
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--output_dir ./output/gpt2-test \
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--save_steps 500 \
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--logging_steps 100 \
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--push_to_hub \
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--hub_model_id "yasutoshi-lab/gpt2-verification"
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--hub_private_repo true \
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--hub_strategy "end"
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```
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## Model description
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More information needed
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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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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 3.0
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### Training results
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### Framework versions
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- Transformers 5.6.0.dev0
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- Pytorch 2.11.0+cu128
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- Datasets 4.8.4
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- Tokenizers 0.22.2
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