metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert-base-Massive-intent_24
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: 0.8558780127889818
bert-base-Massive-intent_24
This model is a fine-tuned version of gokuls/bert_base_24 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.8019
- Accuracy: 0.8559
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 |
|---|---|---|---|---|
| 1.6309 | 1.0 | 180 | 0.9071 | 0.7727 |
| 0.7005 | 2.0 | 360 | 0.6913 | 0.8185 |
| 0.4328 | 3.0 | 540 | 0.6321 | 0.8455 |
| 0.2875 | 4.0 | 720 | 0.6583 | 0.8333 |
| 0.2036 | 5.0 | 900 | 0.6765 | 0.8426 |
| 0.1437 | 6.0 | 1080 | 0.7043 | 0.8446 |
| 0.1088 | 7.0 | 1260 | 0.7193 | 0.8510 |
| 0.0812 | 8.0 | 1440 | 0.7489 | 0.8426 |
| 0.0622 | 9.0 | 1620 | 0.7450 | 0.8495 |
| 0.0453 | 10.0 | 1800 | 0.7722 | 0.8500 |
| 0.0346 | 11.0 | 1980 | 0.7849 | 0.8470 |
| 0.0227 | 12.0 | 2160 | 0.8088 | 0.8515 |
| 0.0166 | 13.0 | 2340 | 0.8019 | 0.8559 |
| 0.0114 | 14.0 | 2520 | 0.7968 | 0.8549 |
| 0.0078 | 15.0 | 2700 | 0.7949 | 0.8549 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3