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--- |
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license: mit |
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base_model: roberta-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imdb |
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metrics: |
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- accuracy |
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model-index: |
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- name: N_roberta_imdb_padding30model |
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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: imdb |
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type: imdb |
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config: plain_text |
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split: test |
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args: plain_text |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.95048 |
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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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# N_roberta_imdb_padding30model |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the imdb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4323 |
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- Accuracy: 0.9505 |
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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: 2e-05 |
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- train_batch_size: 16 |
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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: 20 |
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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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| 0.2137 | 1.0 | 1563 | 0.2731 | 0.9326 | |
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| 0.1664 | 2.0 | 3126 | 0.1977 | 0.9475 | |
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| 0.1079 | 3.0 | 4689 | 0.2742 | 0.9441 | |
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| 0.0728 | 4.0 | 6252 | 0.2245 | 0.9474 | |
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| 0.0479 | 5.0 | 7815 | 0.2897 | 0.9496 | |
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| 0.0405 | 6.0 | 9378 | 0.3329 | 0.9473 | |
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| 0.0428 | 7.0 | 10941 | 0.3308 | 0.9452 | |
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| 0.0285 | 8.0 | 12504 | 0.3586 | 0.9468 | |
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| 0.0242 | 9.0 | 14067 | 0.3599 | 0.9459 | |
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| 0.0193 | 10.0 | 15630 | 0.3755 | 0.9444 | |
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| 0.0133 | 11.0 | 17193 | 0.3994 | 0.9445 | |
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| 0.0178 | 12.0 | 18756 | 0.3940 | 0.9486 | |
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| 0.0081 | 13.0 | 20319 | 0.4090 | 0.9479 | |
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| 0.0064 | 14.0 | 21882 | 0.4170 | 0.9500 | |
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| 0.004 | 15.0 | 23445 | 0.4484 | 0.9434 | |
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| 0.0031 | 16.0 | 25008 | 0.4368 | 0.9484 | |
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| 0.0043 | 17.0 | 26571 | 0.4170 | 0.9496 | |
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| 0.0053 | 18.0 | 28134 | 0.4129 | 0.9501 | |
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| 0.0026 | 19.0 | 29697 | 0.4325 | 0.9498 | |
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| 0.0029 | 20.0 | 31260 | 0.4323 | 0.9505 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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