---
language:
- en
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: SST2
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE SST2
      type: glue
      args: sst2
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9621559633027523
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SST2

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the GLUE SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1664
- Accuracy: 0.9622

## 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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1696        | 1.0   | 1053 | 0.1285          | 0.9507   |
| 0.1166        | 2.0   | 2106 | 0.1410          | 0.9610   |
| 0.0865        | 3.0   | 3159 | 0.1355          | 0.9576   |
| 0.0637        | 4.0   | 4212 | 0.1412          | 0.9587   |
| 0.0468        | 5.0   | 5265 | 0.1664          | 0.9622   |
| 0.0335        | 6.0   | 6318 | 0.1930          | 0.9599   |


### Framework versions

- Transformers 4.43.3
- Pytorch 1.11.0+cu113
- Datasets 2.20.0
- Tokenizers 0.19.1