metadata
base_model: gokuls/HBERTv1_48_L4_H64_A2
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: HBERTv1_48_L4_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: 0.32611903590752583
HBERTv1_48_L4_H64_A2_massive
This model is a fine-tuned version of gokuls/HBERTv1_48_L4_H64_A2 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 2.3014
- Accuracy: 0.3261
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 |
|---|---|---|---|---|
| 4.0 | 1.0 | 180 | 3.8278 | 0.0723 |
| 3.6366 | 2.0 | 360 | 3.4279 | 0.1117 |
| 3.3385 | 3.0 | 540 | 3.1935 | 0.1638 |
| 3.1113 | 4.0 | 720 | 2.9828 | 0.1909 |
| 2.9324 | 5.0 | 900 | 2.8344 | 0.2130 |
| 2.7882 | 6.0 | 1080 | 2.7100 | 0.2523 |
| 2.6832 | 7.0 | 1260 | 2.6215 | 0.2774 |
| 2.5965 | 8.0 | 1440 | 2.5459 | 0.2887 |
| 2.5244 | 9.0 | 1620 | 2.4872 | 0.2966 |
| 2.4603 | 10.0 | 1800 | 2.4261 | 0.3010 |
| 2.3987 | 11.0 | 1980 | 2.3758 | 0.3153 |
| 2.3615 | 12.0 | 2160 | 2.3469 | 0.3217 |
| 2.3292 | 13.0 | 2340 | 2.3241 | 0.3212 |
| 2.3071 | 14.0 | 2520 | 2.3100 | 0.3212 |
| 2.288 | 15.0 | 2700 | 2.3014 | 0.3261 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.0