transformers pytorch tensorboard roberta text-classification generated_from_trainer dataset:massive license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- massive
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilroberta-base-Massive-intent
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: train
      args: en-US
    metrics:
    - type: accuracy
      value: 0.8937530742744713
      name: Accuracy
---

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# distilroberta-base-Massive-intent

This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6618
- Accuracy: 0.8938

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.41          | 1.0   | 720  | 0.6742          | 0.8288   |
| 0.4978        | 2.0   | 1440 | 0.5150          | 0.8751   |
| 0.3009        | 3.0   | 2160 | 0.5705          | 0.8790   |
| 0.1953        | 4.0   | 2880 | 0.5887          | 0.8795   |
| 0.127         | 5.0   | 3600 | 0.6123          | 0.8810   |
| 0.0914        | 6.0   | 4320 | 0.6575          | 0.8834   |
| 0.0583        | 7.0   | 5040 | 0.6618          | 0.8938   |
| 0.0355        | 8.0   | 5760 | 0.7591          | 0.8864   |
| 0.0259        | 9.0   | 6480 | 0.8087          | 0.8780   |
| 0.02          | 10.0  | 7200 | 0.7964          | 0.8888   |


### Framework versions

- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
