metadata
base_model: gokuls/HBERTv1_48_L2_H256_A4
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L2_H256_A4_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: 0.8362026561731432
HBERTv1_48_L2_H256_A4_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L2_H256_A4 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.6816
- Accuracy: 0.8362
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 |
|---|---|---|---|---|
| 3.0609 | 1.0 | 180 | 2.0828 | 0.5416 |
| 1.7322 | 2.0 | 360 | 1.2770 | 0.6995 |
| 1.1671 | 3.0 | 540 | 0.9723 | 0.7521 |
| 0.8923 | 4.0 | 720 | 0.8411 | 0.7723 |
| 0.7282 | 5.0 | 900 | 0.7748 | 0.7890 |
| 0.6334 | 6.0 | 1080 | 0.7396 | 0.8042 |
| 0.5372 | 7.0 | 1260 | 0.7192 | 0.8146 |
| 0.4854 | 8.0 | 1440 | 0.7008 | 0.8229 |
| 0.4327 | 9.0 | 1620 | 0.6971 | 0.8224 |
| 0.3975 | 10.0 | 1800 | 0.6840 | 0.8323 |
| 0.3598 | 11.0 | 1980 | 0.6947 | 0.8313 |
| 0.334 | 12.0 | 2160 | 0.6791 | 0.8337 |
| 0.317 | 13.0 | 2340 | 0.6859 | 0.8323 |
| 0.2969 | 14.0 | 2520 | 0.6816 | 0.8347 |
| 0.2918 | 15.0 | 2700 | 0.6816 | 0.8362 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0