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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: distilbert_sa_GLUE_Experiment_data_aug_mnli_96
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results: []
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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_data_aug_mnli_96
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1396
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- Accuracy: 0.5795
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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 |
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|:-------------:|:-----:|:------:|:---------------:|:--------:|
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| 0.9142 | 1.0 | 31440 | 0.9328 | 0.5686 |
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| 0.8099 | 2.0 | 62880 | 0.9523 | 0.5752 |
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| 0.7371 | 3.0 | 94320 | 1.0072 | 0.5737 |
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| 0.6756 | 4.0 | 125760 | 1.0606 | 0.5750 |
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| 0.6229 | 5.0 | 157200 | 1.1116 | 0.5739 |
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| 0.5784 | 6.0 | 188640 | 1.1396 | 0.5795 |
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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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