metadata
base_model: gokuls/HBERTv1_48_L10_H512_A8
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L10_H512_A8_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: 0.8583374323659616
HBERTv1_48_L10_H512_A8_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L10_H512_A8 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.8593
- Accuracy: 0.8583
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 |
|---|---|---|---|---|
| 2.6536 | 1.0 | 180 | 1.3212 | 0.6542 |
| 1.0696 | 2.0 | 360 | 0.8384 | 0.7777 |
| 0.701 | 3.0 | 540 | 0.7514 | 0.8082 |
| 0.5181 | 4.0 | 720 | 0.7376 | 0.8096 |
| 0.3958 | 5.0 | 900 | 0.6764 | 0.8269 |
| 0.3031 | 6.0 | 1080 | 0.6955 | 0.8382 |
| 0.2378 | 7.0 | 1260 | 0.7173 | 0.8392 |
| 0.1719 | 8.0 | 1440 | 0.7289 | 0.8401 |
| 0.1294 | 9.0 | 1620 | 0.7609 | 0.8485 |
| 0.096 | 10.0 | 1800 | 0.7744 | 0.8465 |
| 0.0769 | 11.0 | 1980 | 0.8206 | 0.8490 |
| 0.05 | 12.0 | 2160 | 0.8085 | 0.8564 |
| 0.034 | 13.0 | 2340 | 0.8537 | 0.8534 |
| 0.0218 | 14.0 | 2520 | 0.8480 | 0.8564 |
| 0.0139 | 15.0 | 2700 | 0.8593 | 0.8583 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0