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--- |
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language: |
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- en |
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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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- glue |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: distilbert_sa_GLUE_Experiment_logit_kd_mrpc_384 |
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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 MRPC |
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type: glue |
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config: mrpc |
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split: validation |
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args: mrpc |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.32598039215686275 |
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- name: F1 |
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type: f1 |
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value: 0.03508771929824561 |
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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_sa_GLUE_Experiment_logit_kd_mrpc_384 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE MRPC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5217 |
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- Accuracy: 0.3260 |
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- F1: 0.0351 |
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- Combined Score: 0.1805 |
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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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- 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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- num_epochs: 50 |
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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 | F1 | Combined Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| |
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| 0.5343 | 1.0 | 15 | 0.5288 | 0.3162 | 0.0 | 0.1581 | |
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| 0.5306 | 2.0 | 30 | 0.5289 | 0.3162 | 0.0 | 0.1581 | |
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| 0.5294 | 3.0 | 45 | 0.5281 | 0.3162 | 0.0 | 0.1581 | |
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| 0.5277 | 4.0 | 60 | 0.5269 | 0.3162 | 0.0 | 0.1581 | |
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| 0.518 | 5.0 | 75 | 0.5217 | 0.3260 | 0.0351 | 0.1805 | |
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| 0.5035 | 6.0 | 90 | 0.5230 | 0.3971 | 0.2635 | 0.3303 | |
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| 0.4866 | 7.0 | 105 | 0.5301 | 0.3652 | 0.1618 | 0.2635 | |
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| 0.4624 | 8.0 | 120 | 0.5491 | 0.5147 | 0.5123 | 0.5135 | |
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| 0.4424 | 9.0 | 135 | 0.5479 | 0.5245 | 0.5530 | 0.5388 | |
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| 0.4295 | 10.0 | 150 | 0.5660 | 0.5392 | 0.5766 | 0.5579 | |
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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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