|
--- |
|
license: apache-2.0 |
|
base_model: google/bert_uncased_L-4_H-128_A-2 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- massive |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert_uncased_L-4_H-128_A-2_massive |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: massive |
|
type: massive |
|
config: en-US |
|
split: validation |
|
args: en-US |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.7122479094933596 |
|
--- |
|
|
|
<!-- 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-4_H-128_A-2_massive |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co./google/bert_uncased_L-4_H-128_A-2) on the massive dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5917 |
|
- Accuracy: 0.7122 |
|
|
|
## 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: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 3.8362 | 1.0 | 180 | 3.5577 | 0.2750 | |
|
| 3.3785 | 2.0 | 360 | 3.1194 | 0.4215 | |
|
| 3.0059 | 3.0 | 540 | 2.7843 | 0.4845 | |
|
| 2.7219 | 4.0 | 720 | 2.5372 | 0.5273 | |
|
| 2.4947 | 5.0 | 900 | 2.3286 | 0.5578 | |
|
| 2.3072 | 6.0 | 1080 | 2.1582 | 0.5947 | |
|
| 2.1494 | 7.0 | 1260 | 2.0276 | 0.6232 | |
|
| 2.0206 | 8.0 | 1440 | 1.9108 | 0.6375 | |
|
| 1.9207 | 9.0 | 1620 | 1.8206 | 0.6704 | |
|
| 1.83 | 10.0 | 1800 | 1.7500 | 0.6891 | |
|
| 1.7592 | 11.0 | 1980 | 1.6872 | 0.7004 | |
|
| 1.7011 | 12.0 | 2160 | 1.6489 | 0.7019 | |
|
| 1.6627 | 13.0 | 2340 | 1.6160 | 0.7093 | |
|
| 1.6347 | 14.0 | 2520 | 1.5992 | 0.7118 | |
|
| 1.6216 | 15.0 | 2700 | 1.5917 | 0.7122 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.34.0 |
|
- Pytorch 1.14.0a0+410ce96 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.14.1 |
|
|
