metadata
license: apache-2.0
base_model: google/bert_uncased_L-2_H-512_A-8
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-2_H-512_A-8_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: 0.8740777176586325
bert_uncased_L-2_H-512_A-8_massive
This model is a fine-tuned version of google/bert_uncased_L-2_H-512_A-8 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.5162
- Accuracy: 0.8741
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 |
|---|---|---|---|---|
| 2.9188 | 1.0 | 180 | 1.8187 | 0.6085 |
| 1.5237 | 2.0 | 360 | 1.0972 | 0.7585 |
| 0.9995 | 3.0 | 540 | 0.8257 | 0.7978 |
| 0.7371 | 4.0 | 720 | 0.6883 | 0.8318 |
| 0.5734 | 5.0 | 900 | 0.6198 | 0.8455 |
| 0.4599 | 6.0 | 1080 | 0.5870 | 0.8569 |
| 0.3835 | 7.0 | 1260 | 0.5654 | 0.8574 |
| 0.3262 | 8.0 | 1440 | 0.5414 | 0.8652 |
| 0.279 | 9.0 | 1620 | 0.5282 | 0.8697 |
| 0.2435 | 10.0 | 1800 | 0.5281 | 0.8677 |
| 0.2199 | 11.0 | 1980 | 0.5156 | 0.8697 |
| 0.1999 | 12.0 | 2160 | 0.5162 | 0.8741 |
| 0.1824 | 13.0 | 2340 | 0.5224 | 0.8736 |
| 0.1712 | 14.0 | 2520 | 0.5223 | 0.8731 |
| 0.1627 | 15.0 | 2700 | 0.5206 | 0.8716 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1