metadata
base_model: gokuls/bert_12_layer_model_v3_complete_training_48
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_12_layer_model_v3_48_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: 0.8607968519429414
bert_12_layer_model_v3_48_massive
This model is a fine-tuned version of gokuls/bert_12_layer_model_v3_complete_training_48 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.9214
- Accuracy: 0.8608
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 |
|---|---|---|---|---|
| 1.7608 | 1.0 | 180 | 0.9351 | 0.7482 |
| 0.8417 | 2.0 | 360 | 0.8314 | 0.7841 |
| 0.6057 | 3.0 | 540 | 0.7307 | 0.8160 |
| 0.4715 | 4.0 | 720 | 0.6995 | 0.8382 |
| 0.3766 | 5.0 | 900 | 0.7602 | 0.8273 |
| 0.2933 | 6.0 | 1080 | 0.7537 | 0.8357 |
| 0.2321 | 7.0 | 1260 | 0.7966 | 0.8426 |
| 0.1873 | 8.0 | 1440 | 0.8015 | 0.8396 |
| 0.1447 | 9.0 | 1620 | 0.8281 | 0.8392 |
| 0.1079 | 10.0 | 1800 | 0.8665 | 0.8446 |
| 0.0781 | 11.0 | 1980 | 0.8758 | 0.8500 |
| 0.0573 | 12.0 | 2160 | 0.8646 | 0.8515 |
| 0.0383 | 13.0 | 2340 | 0.9121 | 0.8603 |
| 0.024 | 14.0 | 2520 | 0.8963 | 0.8593 |
| 0.015 | 15.0 | 2700 | 0.9214 | 0.8608 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1