LABEL_0 LABEL_1 LABEL_2 LABEL_3
---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: rubert-tiny2_finetuned_emotion_experiment_augmented_anger_fear_no_emojis
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# rubert-tiny2_finetuned_emotion_experiment_augmented_anger_fear_no_emojis

This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5820
- Accuracy: 0.7881
- F1: 0.7886
- Precision: 0.7906
- Recall: 0.7881

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0996        | 1.0   | 69   | 1.0013          | 0.6879   | 0.6779 | 0.7070    | 0.6879 |
| 0.9524        | 2.0   | 138  | 0.8651          | 0.7265   | 0.7245 | 0.7322    | 0.7265 |
| 0.8345        | 3.0   | 207  | 0.7821          | 0.7422   | 0.7413 | 0.7445    | 0.7422 |
| 0.7573        | 4.0   | 276  | 0.7222          | 0.7484   | 0.7473 | 0.7482    | 0.7484 |
| 0.6923        | 5.0   | 345  | 0.6828          | 0.7568   | 0.7562 | 0.7562    | 0.7568 |
| 0.6412        | 6.0   | 414  | 0.6531          | 0.7568   | 0.7559 | 0.7556    | 0.7568 |
| 0.5982        | 7.0   | 483  | 0.6320          | 0.7610   | 0.7601 | 0.7597    | 0.7610 |
| 0.5593        | 8.0   | 552  | 0.6133          | 0.7651   | 0.7655 | 0.7664    | 0.7651 |
| 0.5183        | 9.0   | 621  | 0.6036          | 0.7714   | 0.7708 | 0.7709    | 0.7714 |
| 0.5042        | 10.0  | 690  | 0.5951          | 0.7756   | 0.7755 | 0.7760    | 0.7756 |
| 0.483         | 11.0  | 759  | 0.5878          | 0.7766   | 0.7768 | 0.7774    | 0.7766 |
| 0.4531        | 12.0  | 828  | 0.5855          | 0.7850   | 0.7841 | 0.7839    | 0.7850 |
| 0.4386        | 13.0  | 897  | 0.5828          | 0.7797   | 0.7790 | 0.7786    | 0.7797 |
| 0.4238        | 14.0  | 966  | 0.5788          | 0.7777   | 0.7780 | 0.7786    | 0.7777 |
| 0.4018        | 15.0  | 1035 | 0.5793          | 0.7839   | 0.7842 | 0.7855    | 0.7839 |
| 0.3998        | 16.0  | 1104 | 0.5801          | 0.7850   | 0.7844 | 0.7841    | 0.7850 |
| 0.3747        | 17.0  | 1173 | 0.5791          | 0.7839   | 0.7836 | 0.7833    | 0.7839 |
| 0.3595        | 18.0  | 1242 | 0.5799          | 0.7891   | 0.7891 | 0.7894    | 0.7891 |
| 0.3575        | 19.0  | 1311 | 0.5820          | 0.7881   | 0.7886 | 0.7906    | 0.7881 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
