metadata
base_model: gokuls/HBERTv1_48_L2_H64_A2
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L2_H64_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: 0.40088539104771276
HBERTv1_48_L2_H64_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L2_H64_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 2.1655
- Accuracy: 0.4009
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 |
|---|---|---|---|---|
| 3.9873 | 1.0 | 180 | 3.7924 | 0.1190 |
| 3.6056 | 2.0 | 360 | 3.4147 | 0.1210 |
| 3.3391 | 3.0 | 540 | 3.2008 | 0.1422 |
| 3.1518 | 4.0 | 720 | 3.0285 | 0.1977 |
| 2.9855 | 5.0 | 900 | 2.8620 | 0.2356 |
| 2.8224 | 6.0 | 1080 | 2.7059 | 0.2671 |
| 2.6751 | 7.0 | 1260 | 2.5728 | 0.2986 |
| 2.5558 | 8.0 | 1440 | 2.4704 | 0.3399 |
| 2.4664 | 9.0 | 1620 | 2.3848 | 0.3566 |
| 2.3814 | 10.0 | 1800 | 2.3129 | 0.3719 |
| 2.3131 | 11.0 | 1980 | 2.2572 | 0.3792 |
| 2.2662 | 12.0 | 2160 | 2.2149 | 0.3920 |
| 2.2201 | 13.0 | 2340 | 2.1830 | 0.3935 |
| 2.1957 | 14.0 | 2520 | 2.1655 | 0.4009 |
| 2.1831 | 15.0 | 2700 | 2.1585 | 0.3994 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0