---
base_model: cardiffnlp/twitter-roberta-base-emotion
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_roberta-base-on-IEMOCAP_3
  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. -->

# finetuned_roberta-base-on-IEMOCAP_3

This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-emotion](https://huggingface.co/cardiffnlp/twitter-roberta-base-emotion) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0811
- Accuracy: 0.6481

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8961        | 1.0   | 110  | 0.8901          | 0.6435   |
| 0.7964        | 2.0   | 220  | 0.8135          | 0.6731   |
| 0.6132        | 3.0   | 330  | 0.8108          | 0.6993   |
| 0.3977        | 4.0   | 440  | 0.8360          | 0.7198   |
| 0.308         | 5.0   | 550  | 0.8994          | 0.6982   |
| 0.264         | 6.0   | 660  | 1.0231          | 0.6970   |
| 0.2477        | 7.0   | 770  | 1.0716          | 0.6993   |
| 0.1822        | 8.0   | 880  | 1.0890          | 0.6970   |
| 0.1438        | 9.0   | 990  | 1.1732          | 0.7039   |
| 0.1445        | 10.0  | 1100 | 1.2182          | 0.6902   |
| 0.1143        | 11.0  | 1210 | 1.2504          | 0.6993   |
| 0.1266        | 12.0  | 1320 | 1.3046          | 0.6970   |
| 0.094         | 13.0  | 1430 | 1.3148          | 0.7130   |
| 0.0985        | 14.0  | 1540 | 1.3253          | 0.7175   |
| 0.0947        | 15.0  | 1650 | 1.3411          | 0.7118   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1