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--- |
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library_name: transformers |
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language: |
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- en |
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base_model: gokulsrinivasagan/distilbert_lda_50_v1_book |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilbert_lda_50_v1_book_mnli |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: GLUE MNLI |
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type: glue |
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args: mnli |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7891578519121237 |
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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_50_v1_book_mnli |
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This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_50_v1_book](https://huggingface.co/gokulsrinivasagan/distilbert_lda_50_v1_book) on the GLUE MNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5241 |
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- Accuracy: 0.7892 |
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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: 256 |
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- eval_batch_size: 256 |
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- seed: 10 |
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- optimizer: Use 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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- num_epochs: 50 |
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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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| 0.6972 | 1.0 | 1534 | 0.5769 | 0.7673 | |
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| 0.5103 | 2.0 | 3068 | 0.5419 | 0.7843 | |
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| 0.4037 | 3.0 | 4602 | 0.5657 | 0.7867 | |
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| 0.3143 | 4.0 | 6136 | 0.6039 | 0.7947 | |
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| 0.2422 | 5.0 | 7670 | 0.6404 | 0.7900 | |
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| 0.1859 | 6.0 | 9204 | 0.7668 | 0.7873 | |
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| 0.1482 | 7.0 | 10738 | 0.8023 | 0.7903 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.20.3 |
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