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---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-sst-2-64-13-30
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-2-64-13-30
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: 0.8764
- Accuracy: 0.8828
## 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 | 4 | 0.7179 | 0.5 |
| No log | 2.0 | 8 | 0.6981 | 0.5312 |
| 0.717 | 3.0 | 12 | 0.6948 | 0.4688 |
| 0.717 | 4.0 | 16 | 0.7043 | 0.4453 |
| 0.6986 | 5.0 | 20 | 0.6971 | 0.4688 |
| 0.6986 | 6.0 | 24 | 0.7705 | 0.5156 |
| 0.6986 | 7.0 | 28 | 0.7463 | 0.625 |
| 0.6087 | 8.0 | 32 | 0.7016 | 0.6172 |
| 0.6087 | 9.0 | 36 | 0.5869 | 0.7656 |
| 0.5365 | 10.0 | 40 | 0.5156 | 0.8047 |
| 0.5365 | 11.0 | 44 | 0.4578 | 0.8203 |
| 0.5365 | 12.0 | 48 | 0.3511 | 0.9141 |
| 0.3599 | 13.0 | 52 | 0.3583 | 0.8828 |
| 0.3599 | 14.0 | 56 | 0.3759 | 0.8828 |
| 0.1271 | 15.0 | 60 | 0.4324 | 0.8906 |
| 0.1271 | 16.0 | 64 | 0.4806 | 0.8984 |
| 0.1271 | 17.0 | 68 | 0.5256 | 0.875 |
| 0.0516 | 18.0 | 72 | 0.6432 | 0.8906 |
| 0.0516 | 19.0 | 76 | 0.6976 | 0.875 |
| 0.0034 | 20.0 | 80 | 0.8148 | 0.875 |
| 0.0034 | 21.0 | 84 | 0.8401 | 0.8828 |
| 0.0034 | 22.0 | 88 | 0.8721 | 0.8828 |
| 0.0467 | 23.0 | 92 | 0.8001 | 0.8906 |
| 0.0467 | 24.0 | 96 | 0.8580 | 0.8828 |
| 0.0005 | 25.0 | 100 | 0.8849 | 0.875 |
| 0.0005 | 26.0 | 104 | 0.9024 | 0.875 |
| 0.0005 | 27.0 | 108 | 0.9125 | 0.875 |
| 0.0005 | 28.0 | 112 | 0.8686 | 0.8828 |
| 0.0005 | 29.0 | 116 | 0.8764 | 0.8828 |
| 0.0231 | 30.0 | 120 | 0.8764 | 0.8828 |
### Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3
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