readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - snips_built_in_intents
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-finetuned-intent-ipu
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # roberta-base-finetuned-intent-ipu
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the snips_built_in_intents dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1503
  - Accuracy: 1.0
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 1
  - eval_batch_size: 1
  - seed: 42
  - distributed_type: IPU
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 8
  - total_eval_batch_size: 5
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - training precision: Mixed Precision
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.2478        | 1.0   | 75   | 0.6069          | 0.96     |
  | 0.2522        | 2.0   | 150  | 0.1503          | 1.0      |
  | 0.0903        | 3.0   | 225  | 0.0712          | 1.0      |
  | 0.0883        | 4.0   | 300  | 0.0350          | 1.0      |
  | 0.0491        | 5.0   | 375  | 0.0267          | 1.0      |
  | 0.0305        | 6.0   | 450  | 0.0218          | 1.0      |
  | 0.0461        | 7.0   | 525  | 0.0191          | 1.0      |
  | 0.039         | 8.0   | 600  | 0.0174          | 1.0      |
  | 0.0337        | 9.0   | 675  | 0.0166          | 1.0      |
  | 0.0164        | 10.0  | 750  | 0.0162          | 1.0      |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.10.0+cpu
  - Datasets 2.7.1
  - Tokenizers 0.12.0
  