---
base_model: cardiffnlp/twitter-roberta-base-emotion
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_roberta-base-on-IEMOCAP_4
  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_4

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: 1.5143
- Accuracy: 0.6867

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8876        | 1.0   | 113  | 0.9530          | 0.6341   |
| 0.7153        | 2.0   | 226  | 0.8473          | 0.6807   |
| 0.5127        | 3.0   | 339  | 0.8841          | 0.6907   |
| 0.3844        | 4.0   | 452  | 0.9751          | 0.7062   |
| 0.3104        | 5.0   | 565  | 0.9363          | 0.7029   |
| 0.2374        | 6.0   | 678  | 1.1047          | 0.6896   |
| 0.2128        | 7.0   | 791  | 1.1239          | 0.7040   |
| 0.2104        | 8.0   | 904  | 1.1717          | 0.7129   |
| 0.1896        | 9.0   | 1017 | 1.1580          | 0.6973   |
| 0.1211        | 10.0  | 1130 | 1.2320          | 0.7029   |
| 0.1737        | 11.0  | 1243 | 1.3389          | 0.6973   |
| 0.1022        | 12.0  | 1356 | 1.3537          | 0.7062   |
| 0.0934        | 13.0  | 1469 | 1.3742          | 0.7140   |
| 0.0987        | 14.0  | 1582 | 1.4039          | 0.7151   |
| 0.1065        | 15.0  | 1695 | 1.4150          | 0.7173   |


### Framework versions

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