metadata
base_model: gokuls/HBERTv1_48_L4_H768_A12
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L4_H768_A12_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: 0.8726020659124447
HBERTv1_48_L4_H768_A12_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L4_H768_A12 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.7904
- Accuracy: 0.8726
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 |
|---|---|---|---|---|
| 1.714 | 1.0 | 180 | 0.7757 | 0.7826 |
| 0.6529 | 2.0 | 360 | 0.6221 | 0.8328 |
| 0.4238 | 3.0 | 540 | 0.5757 | 0.8544 |
| 0.2832 | 4.0 | 720 | 0.5940 | 0.8544 |
| 0.2056 | 5.0 | 900 | 0.6066 | 0.8495 |
| 0.1417 | 6.0 | 1080 | 0.6677 | 0.8559 |
| 0.0983 | 7.0 | 1260 | 0.6791 | 0.8519 |
| 0.0741 | 8.0 | 1440 | 0.7092 | 0.8495 |
| 0.0495 | 9.0 | 1620 | 0.7061 | 0.8687 |
| 0.0356 | 10.0 | 1800 | 0.7682 | 0.8633 |
| 0.0243 | 11.0 | 1980 | 0.7785 | 0.8623 |
| 0.0144 | 12.0 | 2160 | 0.7833 | 0.8677 |
| 0.0099 | 13.0 | 2340 | 0.7941 | 0.8711 |
| 0.0063 | 14.0 | 2520 | 0.7904 | 0.8726 |
| 0.0037 | 15.0 | 2700 | 0.8014 | 0.8677 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0