transformers pytorch tensorboard roberta text-classification generated_from_trainer dataset:sst2 license:mit model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- sst2
license: mit
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: finetuning-roberta-base-on-sst2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: sst2
      type: sst2
      config: default
      split: validation
      args: default
    metrics:
    - type: accuracy
      value: 0.9415137614678899
      name: Accuracy
    - type: f1
      value: 0.9425028184892897
      name: F1
---

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# finetuning-roberta-base-on-sst2

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the sst2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2207
- Accuracy: 0.9415
- F1: 0.9425

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
