---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-sst-2-16-13-smoothed
  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-sst-2-16-13-smoothed

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5750
- Accuracy: 0.9688

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 75
- label_smoothing_factor: 0.45

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.6919          | 0.5      |
| No log        | 2.0   | 2    | 0.6919          | 0.5      |
| No log        | 3.0   | 3    | 0.6919          | 0.5      |
| No log        | 4.0   | 4    | 0.6919          | 0.5      |
| No log        | 5.0   | 5    | 0.6919          | 0.5      |
| No log        | 6.0   | 6    | 0.6918          | 0.5      |
| No log        | 7.0   | 7    | 0.6918          | 0.5      |
| No log        | 8.0   | 8    | 0.6918          | 0.5      |
| No log        | 9.0   | 9    | 0.6918          | 0.5      |
| 0.6949        | 10.0  | 10   | 0.6917          | 0.5      |
| 0.6949        | 11.0  | 11   | 0.6917          | 0.5      |
| 0.6949        | 12.0  | 12   | 0.6916          | 0.5      |
| 0.6949        | 13.0  | 13   | 0.6916          | 0.5      |
| 0.6949        | 14.0  | 14   | 0.6915          | 0.5      |
| 0.6949        | 15.0  | 15   | 0.6914          | 0.5      |
| 0.6949        | 16.0  | 16   | 0.6914          | 0.5312   |
| 0.6949        | 17.0  | 17   | 0.6913          | 0.5312   |
| 0.6949        | 18.0  | 18   | 0.6912          | 0.5312   |
| 0.6949        | 19.0  | 19   | 0.6911          | 0.625    |
| 0.6926        | 20.0  | 20   | 0.6910          | 0.625    |
| 0.6926        | 21.0  | 21   | 0.6909          | 0.6562   |
| 0.6926        | 22.0  | 22   | 0.6907          | 0.6875   |
| 0.6926        | 23.0  | 23   | 0.6906          | 0.6875   |
| 0.6926        | 24.0  | 24   | 0.6904          | 0.6875   |
| 0.6926        | 25.0  | 25   | 0.6902          | 0.75     |
| 0.6926        | 26.0  | 26   | 0.6899          | 0.75     |
| 0.6926        | 27.0  | 27   | 0.6896          | 0.75     |
| 0.6926        | 28.0  | 28   | 0.6893          | 0.7188   |
| 0.6926        | 29.0  | 29   | 0.6890          | 0.6875   |
| 0.687         | 30.0  | 30   | 0.6885          | 0.6875   |
| 0.687         | 31.0  | 31   | 0.6880          | 0.7188   |
| 0.687         | 32.0  | 32   | 0.6874          | 0.7188   |
| 0.687         | 33.0  | 33   | 0.6866          | 0.7188   |
| 0.687         | 34.0  | 34   | 0.6857          | 0.7188   |
| 0.687         | 35.0  | 35   | 0.6846          | 0.75     |
| 0.687         | 36.0  | 36   | 0.6832          | 0.75     |
| 0.687         | 37.0  | 37   | 0.6814          | 0.7812   |
| 0.687         | 38.0  | 38   | 0.6791          | 0.7812   |
| 0.687         | 39.0  | 39   | 0.6761          | 0.875    |
| 0.6732        | 40.0  | 40   | 0.6721          | 0.9062   |
| 0.6732        | 41.0  | 41   | 0.6670          | 0.9062   |
| 0.6732        | 42.0  | 42   | 0.6601          | 0.9062   |
| 0.6732        | 43.0  | 43   | 0.6510          | 0.875    |
| 0.6732        | 44.0  | 44   | 0.6392          | 0.875    |
| 0.6732        | 45.0  | 45   | 0.6248          | 0.875    |
| 0.6732        | 46.0  | 46   | 0.6098          | 0.875    |
| 0.6732        | 47.0  | 47   | 0.5961          | 0.875    |
| 0.6732        | 48.0  | 48   | 0.5884          | 0.9375   |
| 0.6732        | 49.0  | 49   | 0.5833          | 0.9375   |
| 0.5913        | 50.0  | 50   | 0.5795          | 0.9062   |
| 0.5913        | 51.0  | 51   | 0.5851          | 0.9062   |
| 0.5913        | 52.0  | 52   | 0.5985          | 0.875    |
| 0.5913        | 53.0  | 53   | 0.6110          | 0.8125   |
| 0.5913        | 54.0  | 54   | 0.6092          | 0.8438   |
| 0.5913        | 55.0  | 55   | 0.6007          | 0.8438   |
| 0.5913        | 56.0  | 56   | 0.5904          | 0.875    |
| 0.5913        | 57.0  | 57   | 0.5846          | 0.9062   |
| 0.5913        | 58.0  | 58   | 0.5829          | 0.9062   |
| 0.5913        | 59.0  | 59   | 0.5843          | 0.9062   |
| 0.544         | 60.0  | 60   | 0.5900          | 0.8438   |
| 0.544         | 61.0  | 61   | 0.5970          | 0.8438   |
| 0.544         | 62.0  | 62   | 0.6026          | 0.8438   |
| 0.544         | 63.0  | 63   | 0.6030          | 0.8438   |
| 0.544         | 64.0  | 64   | 0.5980          | 0.8438   |
| 0.544         | 65.0  | 65   | 0.5901          | 0.8438   |
| 0.544         | 66.0  | 66   | 0.5843          | 0.875    |
| 0.544         | 67.0  | 67   | 0.5800          | 0.9062   |
| 0.544         | 68.0  | 68   | 0.5779          | 0.9375   |
| 0.544         | 69.0  | 69   | 0.5765          | 0.9375   |
| 0.5383        | 70.0  | 70   | 0.5758          | 0.9688   |
| 0.5383        | 71.0  | 71   | 0.5754          | 0.9688   |
| 0.5383        | 72.0  | 72   | 0.5752          | 0.9688   |
| 0.5383        | 73.0  | 73   | 0.5751          | 0.9688   |
| 0.5383        | 74.0  | 74   | 0.5750          | 0.9688   |
| 0.5383        | 75.0  | 75   | 0.5750          | 0.9688   |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3