metadata
base_model: cardiffnlp/twitter-roberta-base-emotion
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned_roberta-base-on-IEMOCAP_3
results: []
finetuned_roberta-base-on-IEMOCAP_3
This model is a fine-tuned version of 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