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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/bert_base_lda_20_v1 |
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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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- matthews_correlation |
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- accuracy |
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model-index: |
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- name: bert_base_lda_20_v1_cola |
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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 COLA |
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type: glue |
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args: cola |
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metrics: |
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- name: Matthews Correlation |
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type: matthews_correlation |
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value: 0.0 |
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- name: Accuracy |
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type: accuracy |
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value: 0.6912751793861389 |
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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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# bert_base_lda_20_v1_cola |
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This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_20_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_20_v1) on the GLUE COLA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6199 |
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- Matthews Correlation: 0.0 |
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- Accuracy: 0.6913 |
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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 | Matthews Correlation | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:| |
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| 0.6136 | 1.0 | 34 | 0.6265 | 0.0 | 0.6913 | |
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| 0.6112 | 2.0 | 68 | 0.6199 | 0.0 | 0.6913 | |
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| 0.5873 | 3.0 | 102 | 0.6349 | 0.0699 | 0.6414 | |
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| 0.5381 | 4.0 | 136 | 0.6502 | 0.1054 | 0.5964 | |
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| 0.4951 | 5.0 | 170 | 0.6613 | 0.0768 | 0.6443 | |
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| 0.4506 | 6.0 | 204 | 0.7529 | 0.1282 | 0.5810 | |
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| 0.4248 | 7.0 | 238 | 0.7049 | 0.0539 | 0.6395 | |
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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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