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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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- gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-5 |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilbert_lda_5_v1 |
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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: gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-5 |
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type: gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-5 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5803243487596768 |
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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_lda_5_v1 |
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This model is a fine-tuned version of [](https://huggingface.co/) on the gokulsrinivasagan/processed_wikitext-103-raw-v1-ld-5 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6788 |
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- Accuracy: 0.5803 |
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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: 0.0001 |
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- train_batch_size: 96 |
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- eval_batch_size: 96 |
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- seed: 10 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH 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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- lr_scheduler_warmup_steps: 10000 |
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- num_epochs: 25 |
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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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| 7.6763 | 4.1982 | 10000 | 7.6034 | 0.1522 | |
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| 6.8215 | 8.3963 | 20000 | 6.3711 | 0.2653 | |
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| 4.1639 | 12.5945 | 30000 | 4.0536 | 0.5321 | |
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| 3.88 | 16.7926 | 40000 | 3.7792 | 0.5683 | |
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| 3.7563 | 20.9908 | 50000 | 3.6849 | 0.5794 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.1 |
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