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--- |
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license: apache-2.0 |
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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: distilbert_add_pre-training-dim-96 |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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dataset: |
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name: wikitext wikitext-103-raw-v1 |
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type: wikitext |
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config: wikitext-103-raw-v1 |
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split: validation |
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args: wikitext-103-raw-v1 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.14942141332434558 |
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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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# distilbert_add_pre-training-dim-96 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wikitext wikitext-103-raw-v1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.6092 |
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- Accuracy: 0.1494 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 14.685 | 1.0 | 3573 | 9.3922 | 0.1240 | |
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| 8.0255 | 2.0 | 7146 | 7.1510 | 0.1315 | |
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| 7.0152 | 3.0 | 10719 | 6.7861 | 0.1482 | |
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| 6.8127 | 4.0 | 14292 | 6.7053 | 0.1493 | |
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| 6.74 | 5.0 | 17865 | 6.6695 | 0.1474 | |
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| 6.7067 | 6.0 | 21438 | 6.6431 | 0.1491 | |
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| 6.6871 | 7.0 | 25011 | 6.6204 | 0.1483 | |
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| 6.6748 | 8.0 | 28584 | 6.6250 | 0.1473 | |
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| 6.6649 | 9.0 | 32157 | 6.6108 | 0.1486 | |
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| 6.6596 | 10.0 | 35730 | 6.6140 | 0.1497 | |
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| 6.6536 | 11.0 | 39303 | 6.6067 | 0.1493 | |
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| 6.6483 | 12.0 | 42876 | 6.6140 | 0.1489 | |
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| 6.6463 | 13.0 | 46449 | 6.6096 | 0.1484 | |
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| 6.6434 | 14.0 | 50022 | 6.5570 | 0.1526 | |
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| 6.6414 | 15.0 | 53595 | 6.5836 | 0.1526 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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