---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-sst-2-32-13-30
  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-2-32-13-30

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: 0.8494
- Accuracy: 0.6406

## 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   | 2    | 0.7123          | 0.5      |
| No log        | 2.0   | 4    | 0.7030          | 0.5      |
| No log        | 3.0   | 6    | 0.6935          | 0.5      |
| No log        | 4.0   | 8    | 0.6906          | 0.5312   |
| 0.718         | 5.0   | 10   | 0.6893          | 0.6094   |
| 0.718         | 6.0   | 12   | 0.6883          | 0.5625   |
| 0.718         | 7.0   | 14   | 0.6860          | 0.5469   |
| 0.718         | 8.0   | 16   | 0.6811          | 0.6094   |
| 0.718         | 9.0   | 18   | 0.6780          | 0.5781   |
| 0.6565        | 10.0  | 20   | 0.6859          | 0.5469   |
| 0.6565        | 11.0  | 22   | 0.6943          | 0.5469   |
| 0.6565        | 12.0  | 24   | 0.7061          | 0.5469   |
| 0.6565        | 13.0  | 26   | 0.6963          | 0.5469   |
| 0.6565        | 14.0  | 28   | 0.7058          | 0.5781   |
| 0.5726        | 15.0  | 30   | 0.7036          | 0.5938   |
| 0.5726        | 16.0  | 32   | 0.7185          | 0.6094   |
| 0.5726        | 17.0  | 34   | 0.7307          | 0.6094   |
| 0.5726        | 18.0  | 36   | 0.7743          | 0.6094   |
| 0.5726        | 19.0  | 38   | 0.7790          | 0.5938   |
| 0.4219        | 20.0  | 40   | 0.7805          | 0.6094   |
| 0.4219        | 21.0  | 42   | 0.7744          | 0.6094   |
| 0.4219        | 22.0  | 44   | 0.7960          | 0.5938   |
| 0.4219        | 23.0  | 46   | 0.8495          | 0.6094   |
| 0.4219        | 24.0  | 48   | 0.8893          | 0.5938   |
| 0.3261        | 25.0  | 50   | 0.8901          | 0.625    |
| 0.3261        | 26.0  | 52   | 0.8924          | 0.625    |
| 0.3261        | 27.0  | 54   | 0.8908          | 0.6094   |
| 0.3261        | 28.0  | 56   | 0.8769          | 0.6094   |
| 0.3261        | 29.0  | 58   | 0.8592          | 0.6094   |
| 0.2415        | 30.0  | 60   | 0.8494          | 0.6406   |


### Framework versions

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