metadata
base_model: gokuls/HBERTv1_48_L8_H64_A2
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L8_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: 0.45056566650270535
HBERTv1_48_L8_H64_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L8_H64_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 2.0023
- Accuracy: 0.4506
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 |
|---|---|---|---|---|
| 3.9694 | 1.0 | 180 | 3.7614 | 0.0949 |
| 3.5709 | 2.0 | 360 | 3.3717 | 0.1323 |
| 3.2745 | 3.0 | 540 | 3.1313 | 0.1968 |
| 3.0491 | 4.0 | 720 | 2.9227 | 0.2086 |
| 2.8486 | 5.0 | 900 | 2.7431 | 0.2238 |
| 2.6671 | 6.0 | 1080 | 2.5865 | 0.2848 |
| 2.514 | 7.0 | 1260 | 2.4468 | 0.3212 |
| 2.3707 | 8.0 | 1440 | 2.3252 | 0.3620 |
| 2.262 | 9.0 | 1620 | 2.2383 | 0.3866 |
| 2.1746 | 10.0 | 1800 | 2.1570 | 0.4171 |
| 2.0999 | 11.0 | 1980 | 2.1083 | 0.4309 |
| 2.0442 | 12.0 | 2160 | 2.0581 | 0.4383 |
| 1.9992 | 13.0 | 2340 | 2.0297 | 0.4432 |
| 1.9728 | 14.0 | 2520 | 2.0104 | 0.4461 |
| 1.9461 | 15.0 | 2700 | 2.0023 | 0.4506 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0