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---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-tiny-4l-10M
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-tiny-4l-10M
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.3432
- Accuracy: 0.0513
## 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: 0.0007
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 128
- total_train_batch_size: 2048
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 100.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.4785 | 4.16 | 50 | 7.3834 | 0.0514 |
| 7.425 | 8.33 | 100 | 7.3559 | 0.0514 |
| 7.4187 | 12.49 | 150 | 7.3517 | 0.0512 |
| 7.4204 | 16.66 | 200 | 7.3440 | 0.0514 |
| 7.4099 | 20.82 | 250 | 7.3454 | 0.0515 |
| 7.2916 | 24.99 | 300 | 7.3442 | 0.0515 |
| 7.4117 | 29.16 | 350 | 7.3440 | 0.0513 |
### Framework versions
- Transformers 4.24.0
- Pytorch 1.11.0+cu113
- Datasets 2.6.1
- Tokenizers 0.12.1
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