|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- emotion |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- precision |
|
model-index: |
|
- name: bert-base-uncased_emotion_ft |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: emotion |
|
type: emotion |
|
config: split |
|
split: validation |
|
args: split |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9355 |
|
- name: F1 |
|
type: f1 |
|
value: 0.9356618127644594 |
|
- name: Precision |
|
type: precision |
|
value: 0.9107946719559769 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# bert-base-uncased_emotion_ft |
|
|
|
This model was trained from scratch on the emotion dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1553 |
|
- Accuracy: 0.9355 |
|
- F1: 0.9357 |
|
- Precision: 0.9108 |
|
|
|
## 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: 64 |
|
- eval_batch_size: 64 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 4 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:| |
|
| 0.82 | 1.0 | 250 | 0.2697 | 0.9105 | 0.9112 | 0.8759 | |
|
| 0.2002 | 2.0 | 500 | 0.1846 | 0.9325 | 0.9331 | 0.9059 | |
|
| 0.1237 | 3.0 | 750 | 0.1562 | 0.9365 | 0.9368 | 0.9120 | |
|
| 0.097 | 4.0 | 1000 | 0.1553 | 0.9355 | 0.9357 | 0.9108 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu117 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|