---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-tiny-8l-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-8l-10M

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.3389
- Accuracy: 0.0516

## 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: 0.0004
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 7.8102        | 1.04  | 50   | 7.3747          | 0.0514   |
| 7.805         | 2.08  | 100  | 7.3699          | 0.0517   |
| 7.7907        | 3.12  | 150  | 7.3595          | 0.0517   |
| 7.7838        | 4.16  | 200  | 7.3617          | 0.0514   |
| 7.7706        | 5.21  | 250  | 7.3586          | 0.0514   |
| 7.2933        | 6.25  | 300  | 7.3566          | 0.0513   |
| 7.2932        | 7.29  | 350  | 7.3527          | 0.0516   |
| 7.2986        | 8.33  | 400  | 7.3561          | 0.0516   |
| 7.289         | 9.37  | 450  | 7.3495          | 0.0515   |
| 7.2879        | 10.41 | 500  | 7.3455          | 0.0514   |
| 7.276         | 11.45 | 550  | 7.3477          | 0.0513   |
| 7.3072        | 12.49 | 600  | 7.3446          | 0.0516   |
| 7.2978        | 13.53 | 650  | 7.3463          | 0.0514   |
| 7.2857        | 14.58 | 700  | 7.3426          | 0.0515   |
| 7.2868        | 15.62 | 750  | 7.3438          | 0.0515   |
| 7.2973        | 16.66 | 800  | 7.3442          | 0.0517   |
| 7.2988        | 17.7  | 850  | 7.3437          | 0.0512   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.11.0+cu113
- Datasets 2.6.1
- Tokenizers 0.12.1