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---
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
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