---
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