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--- |
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license: mit |
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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: roberta-large-sst2 |
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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 SST2 |
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type: glue |
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args: sst2 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9644495412844036 |
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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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# roberta-large-sst2 |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1400 |
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- Accuracy: 0.9644 |
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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: 32 |
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- seed: 42 |
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- distributed_type: sagemaker_data_parallel |
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- num_devices: 8 |
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- total_train_batch_size: 256 |
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- total_eval_batch_size: 256 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 4 |
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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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| 0.3688 | 1.0 | 264 | 0.1444 | 0.9564 | |
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| 0.1529 | 2.0 | 528 | 0.1502 | 0.9518 | |
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| 0.107 | 3.0 | 792 | 0.1388 | 0.9530 | |
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| 0.0666 | 4.0 | 1056 | 0.1400 | 0.9644 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.2+cu113 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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