---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: tiny_focal_alpah
  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. -->

# tiny_focal_alpah

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0492
- Precision: 0.6951
- Recall: 0.6796
- F1: 0.6873
- Accuracy: 0.9512

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0588        | 1.0   | 5561  | 0.0548          | 0.6801    | 0.6235 | 0.6506 | 0.9453   |
| 0.054         | 2.0   | 11122 | 0.0521          | 0.6850    | 0.6478 | 0.6659 | 0.9476   |
| 0.0525        | 3.0   | 16683 | 0.0509          | 0.6834    | 0.6676 | 0.6754 | 0.9486   |
| 0.0492        | 4.0   | 22244 | 0.0503          | 0.6829    | 0.6754 | 0.6791 | 0.9491   |
| 0.0482        | 5.0   | 27805 | 0.0500          | 0.6917    | 0.6727 | 0.6820 | 0.9501   |
| 0.0471        | 6.0   | 33366 | 0.0491          | 0.7085    | 0.6546 | 0.6805 | 0.9510   |
| 0.0459        | 7.0   | 38927 | 0.0486          | 0.6964    | 0.6746 | 0.6853 | 0.9510   |
| 0.0448        | 8.0   | 44488 | 0.0495          | 0.6922    | 0.6813 | 0.6867 | 0.9509   |
| 0.044         | 9.0   | 50049 | 0.0491          | 0.6961    | 0.6755 | 0.6857 | 0.9511   |
| 0.0433        | 10.0  | 55610 | 0.0492          | 0.6951    | 0.6796 | 0.6873 | 0.9512   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1