license: apache-2.0 | |
tags: | |
- generated_from_trainer | |
datasets: | |
- emotion | |
metrics: | |
- accuracy | |
model-index: | |
- name: twitter_emotions | |
results: | |
- task: | |
name: Text Classification | |
type: text-classification | |
dataset: | |
name: emotion | |
type: emotion | |
args: default | |
metrics: | |
- name: Accuracy | |
type: accuracy | |
value: 0.9375 | |
<!-- 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. --> | |
# twitter_emotions | |
This model is a fine-tuned version of [sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co./sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2) on the emotion dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.1647 | |
- Accuracy: 0.9375 | |
## 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: 5e-05 | |
- train_batch_size: 8 | |
- eval_batch_size: 8 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 3.0 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
|:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| 0.2486 | 1.0 | 2000 | 0.2115 | 0.931 | | |
| 0.135 | 2.0 | 4000 | 0.1725 | 0.936 | | |
| 0.1041 | 3.0 | 6000 | 0.1647 | 0.9375 | | |
### Framework versions | |
- Transformers 4.12.5 | |
- Pytorch 1.10.0+cu111 | |
- Datasets 1.15.1 | |
- Tokenizers 0.10.3 | |