|
--- |
|
license: apache-2.0 |
|
base_model: google/bert_uncased_L-10_H-768_A-12 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- emotion |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert_uncased_L-10_H-768_A-12_emotion |
|
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: 0.941 |
|
--- |
|
|
|
<!-- 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_uncased_L-10_H-768_A-12_emotion |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-10_H-768_A-12](https://huggingface.co/google/bert_uncased_L-10_H-768_A-12) on the emotion dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2108 |
|
- Accuracy: 0.941 |
|
|
|
## 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: 64 |
|
- eval_batch_size: 64 |
|
- seed: 33 |
|
- distributed_type: multi-GPU |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.4839 | 1.0 | 250 | 0.1626 | 0.9375 | |
|
| 0.1446 | 2.0 | 500 | 0.1273 | 0.938 | |
|
| 0.1018 | 3.0 | 750 | 0.1331 | 0.9375 | |
|
| 0.0835 | 4.0 | 1000 | 0.1562 | 0.9395 | |
|
| 0.0688 | 5.0 | 1250 | 0.1724 | 0.94 | |
|
| 0.0487 | 6.0 | 1500 | 0.2108 | 0.941 | |
|
| 0.0315 | 7.0 | 1750 | 0.2439 | 0.9375 | |
|
| 0.0201 | 8.0 | 2000 | 0.2511 | 0.9395 | |
|
| 0.0128 | 9.0 | 2250 | 0.2772 | 0.934 | |
|
| 0.0086 | 10.0 | 2500 | 0.2811 | 0.939 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
