---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-sst-2-16-13-30
  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-large-sst-2-16-13-30

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6901
- Accuracy: 0.625

## 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: 1.5e-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: 5
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.6957          | 0.5      |
| No log        | 2.0   | 2    | 0.6955          | 0.5      |
| No log        | 3.0   | 3    | 0.6952          | 0.5      |
| No log        | 4.0   | 4    | 0.6944          | 0.5      |
| No log        | 5.0   | 5    | 0.6937          | 0.5      |
| No log        | 6.0   | 6    | 0.6933          | 0.5      |
| No log        | 7.0   | 7    | 0.6929          | 0.5      |
| No log        | 8.0   | 8    | 0.6942          | 0.5      |
| No log        | 9.0   | 9    | 0.6931          | 0.5      |
| 0.6903        | 10.0  | 10   | 0.6917          | 0.5      |
| 0.6903        | 11.0  | 11   | 0.6905          | 0.5      |
| 0.6903        | 12.0  | 12   | 0.6891          | 0.5312   |
| 0.6903        | 13.0  | 13   | 0.6883          | 0.625    |
| 0.6903        | 14.0  | 14   | 0.6874          | 0.6562   |
| 0.6903        | 15.0  | 15   | 0.6849          | 0.5312   |
| 0.6903        | 16.0  | 16   | 0.6822          | 0.5312   |
| 0.6903        | 17.0  | 17   | 0.6790          | 0.5      |
| 0.6903        | 18.0  | 18   | 0.6742          | 0.5      |
| 0.6903        | 19.0  | 19   | 0.6650          | 0.5312   |
| 0.626         | 20.0  | 20   | 0.6524          | 0.5312   |
| 0.626         | 21.0  | 21   | 0.6444          | 0.5312   |
| 0.626         | 22.0  | 22   | 0.6361          | 0.5625   |
| 0.626         | 23.0  | 23   | 0.6327          | 0.5938   |
| 0.626         | 24.0  | 24   | 0.6337          | 0.625    |
| 0.626         | 25.0  | 25   | 0.6437          | 0.625    |
| 0.626         | 26.0  | 26   | 0.6580          | 0.6562   |
| 0.626         | 27.0  | 27   | 0.6725          | 0.6562   |
| 0.626         | 28.0  | 28   | 0.6812          | 0.625    |
| 0.626         | 29.0  | 29   | 0.6873          | 0.625    |
| 0.4393        | 30.0  | 30   | 0.6901          | 0.625    |


### Framework versions

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