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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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- snips_built_in_intents |
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metrics: |
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- accuracy |
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model-index: |
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- name: roberta-base-finetuned-intent |
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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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# roberta-base-finetuned-intent |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the snips_built_in_intents dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2720 |
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- Accuracy: 0.9333 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: IPU |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 5 |
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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: 10 |
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- training precision: Mixed Precision |
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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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| 1.9568 | 1.0 | 37 | 1.7598 | 0.4333 | |
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| 1.2238 | 2.0 | 74 | 0.8130 | 0.7667 | |
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| 0.4536 | 3.0 | 111 | 0.4985 | 0.8 | |
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| 0.2478 | 4.0 | 148 | 0.3535 | 0.8667 | |
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| 0.0903 | 5.0 | 185 | 0.3110 | 0.8667 | |
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| 0.0849 | 6.0 | 222 | 0.2720 | 0.9333 | |
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| 0.0708 | 7.0 | 259 | 0.2742 | 0.8667 | |
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| 0.0796 | 8.0 | 296 | 0.2839 | 0.8667 | |
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| 0.0638 | 9.0 | 333 | 0.2949 | 0.8667 | |
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| 0.0566 | 10.0 | 370 | 0.2925 | 0.8667 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.10.0+cpu |
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- Datasets 2.7.1 |
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- Tokenizers 0.12.0 |
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