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--- |
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library_name: transformers |
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base_model: /fs-computility/plm/linzhouhan/daibeiya/models/gpt2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- openwebtext |
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model-index: |
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- name: gpt2_base_contextlm_l0212_add_lnnorm_wodetach_v2_lr_bf16_lr1e-3 |
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results: [] |
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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_base_contextlm_l0212_add_lnnorm_wodetach_v2_lr_bf16_lr1e-3 |
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This model is a fine-tuned version of [/fs-computility/plm/linzhouhan/daibeiya/models/gpt2](https://huggingface.co//fs-computility/plm/linzhouhan/daibeiya/models/gpt2) on the openwebtext dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.0300 |
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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: 0.001 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 16 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 512 |
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- total_eval_batch_size: 128 |
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- optimizer: Use adamw_torch with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 3.9616 | 0.0580 | 1000 | 3.8911 | |
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| 3.5512 | 0.1160 | 2000 | 3.4861 | |
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| 3.4279 | 0.1741 | 3000 | 3.3560 | |
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| 3.3471 | 0.2321 | 4000 | 3.2811 | |
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| 3.2957 | 0.2901 | 5000 | 3.2321 | |
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| 3.2677 | 0.3481 | 6000 | 3.1945 | |
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| 3.225 | 0.4062 | 7000 | 3.1653 | |
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| 3.2051 | 0.4642 | 8000 | 3.1390 | |
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| 3.1816 | 0.5222 | 9000 | 3.1161 | |
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| 3.1583 | 0.5802 | 10000 | 3.0971 | |
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| 3.1464 | 0.6383 | 11000 | 3.0794 | |
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| 3.1365 | 0.6963 | 12000 | 3.0645 | |
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| 3.1256 | 0.7543 | 13000 | 3.0509 | |
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| 3.1073 | 0.8123 | 14000 | 3.0417 | |
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| 3.108 | 0.8703 | 15000 | 3.0349 | |
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| 3.098 | 0.9284 | 16000 | 3.0312 | |
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| 3.092 | 0.9864 | 17000 | 3.0301 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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