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--- |
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language: |
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- en |
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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: randomcomb_mlm_ep5_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: 0.8615744507729862 |
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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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# randomcomb_mlm_ep5_mnli |
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This model is a fine-tuned version of [cuenb](https://huggingface.co/joey234/cuenb) on the GLUE MNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4416 |
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- Accuracy: 0.8616 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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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- num_epochs: 3.0 |
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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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| 0.5569 | 0.41 | 5000 | 0.4415 | 0.8273 | |
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| 0.4598 | 0.81 | 10000 | 0.4234 | 0.8425 | |
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| 0.3832 | 1.22 | 15000 | 0.4398 | 0.8475 | |
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| 0.3314 | 1.63 | 20000 | 0.4137 | 0.8494 | |
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| 0.3158 | 2.04 | 25000 | 0.4484 | 0.8527 | |
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| 0.2294 | 2.44 | 30000 | 0.4471 | 0.8552 | |
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| 0.2283 | 2.85 | 35000 | 0.4541 | 0.8557 | |
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### Framework versions |
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- Transformers 4.21.0.dev0 |
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- Pytorch 1.8.0 |
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- Datasets 1.18.3 |
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- Tokenizers 0.12.1 |
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