metadata
base_model: gokuls/HBERTv1_48_L8_H128_A2
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L8_H128_A2_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: 0.7732415150024594
HBERTv1_48_L8_H128_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L8_H128_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.9536
- Accuracy: 0.7732
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 |
|---|---|---|---|---|
| 3.6754 | 1.0 | 180 | 3.1304 | 0.2066 |
| 2.7764 | 2.0 | 360 | 2.3806 | 0.4191 |
| 2.1831 | 3.0 | 540 | 1.9090 | 0.5312 |
| 1.7788 | 4.0 | 720 | 1.5949 | 0.6016 |
| 1.4936 | 5.0 | 900 | 1.4032 | 0.6513 |
| 1.2858 | 6.0 | 1080 | 1.2747 | 0.6847 |
| 1.1232 | 7.0 | 1260 | 1.1651 | 0.7172 |
| 1.0058 | 8.0 | 1440 | 1.0993 | 0.7295 |
| 0.9035 | 9.0 | 1620 | 1.0379 | 0.7486 |
| 0.8245 | 10.0 | 1800 | 1.0164 | 0.7634 |
| 0.7634 | 11.0 | 1980 | 0.9935 | 0.7614 |
| 0.7116 | 12.0 | 2160 | 0.9657 | 0.7708 |
| 0.6763 | 13.0 | 2340 | 0.9624 | 0.7708 |
| 0.6477 | 14.0 | 2520 | 0.9536 | 0.7732 |
| 0.6258 | 15.0 | 2700 | 0.9487 | 0.7732 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0