LABEL_0 LABEL_1 LABEL_2 LABEL_3
---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: distilrubert-tiny-cased-conversational-v1_best_finetuned_emotion_experiment_augmented_anger_fear
  results: []
---

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# distilrubert-tiny-cased-conversational-v1_best_finetuned_emotion_experiment_augmented_anger_fear

This model is a fine-tuned version of [DeepPavlov/distilrubert-tiny-cased-conversational-v1](https://huggingface.co/DeepPavlov/distilrubert-tiny-cased-conversational-v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5751
- Accuracy: 0.8716
- F1: 0.8713
- Precision: 0.8721
- Recall: 0.8716

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8851        | 1.0   | 69   | 0.4740          | 0.8361   | 0.8346 | 0.8364    | 0.8361 |
| 0.4404        | 2.0   | 138  | 0.4018          | 0.8643   | 0.8625 | 0.8672    | 0.8643 |
| 0.305         | 3.0   | 207  | 0.3754          | 0.8800   | 0.8795 | 0.8794    | 0.8800 |
| 0.2441        | 4.0   | 276  | 0.3942          | 0.8758   | 0.8748 | 0.8752    | 0.8758 |
| 0.1837        | 5.0   | 345  | 0.4005          | 0.8873   | 0.8870 | 0.8877    | 0.8873 |
| 0.1573        | 6.0   | 414  | 0.4468          | 0.8716   | 0.8718 | 0.8730    | 0.8716 |
| 0.1292        | 7.0   | 483  | 0.4582          | 0.8747   | 0.8750 | 0.8758    | 0.8747 |
| 0.0949        | 8.0   | 552  | 0.5110          | 0.8601   | 0.8601 | 0.8628    | 0.8601 |
| 0.0729        | 9.0   | 621  | 0.5415          | 0.8674   | 0.8674 | 0.8681    | 0.8674 |
| 0.058         | 10.0  | 690  | 0.5751          | 0.8716   | 0.8713 | 0.8721    | 0.8716 |


### Framework versions

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