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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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- 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: 0.2339
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- Accuracy: 1.0
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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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| 1.9236 | 1.0 | 37 | 1.6689 | 0.3667 |
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| 0.9259 | 2.0 | 74 | 0.7197 | 0.8333 |
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| 0.4666 | 3.0 | 111 | 0.2339 | 1.0 |
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| 0.1732 | 4.0 | 148 | 0.1144 | 1.0 |
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| 0.1412 | 5.0 | 185 | 0.0724 | 1.0 |
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| 0.1023 | 6.0 | 222 | 0.0536 | 1.0 |
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| 0.0772 | 7.0 | 259 | 0.0453 | 1.0 |
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| 0.0786 | 8.0 | 296 | 0.0396 | 1.0 |
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| 0.0581 | 9.0 | 333 | 0.0374 | 1.0 |
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| 0.0553 | 10.0 | 370 | 0.0364 | 1.0 |
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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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