|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- massive |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: bert-tiny-Massive-intent-KD-BERT |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: massive |
|
type: massive |
|
config: en-US |
|
split: train |
|
args: en-US |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.853418593212002 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# bert-tiny-Massive-intent-KD-BERT |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the massive dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8380 |
|
- Accuracy: 0.8534 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 16 |
|
- seed: 33 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 50 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 5.83 | 1.0 | 720 | 4.8826 | 0.3050 | |
|
| 4.7602 | 2.0 | 1440 | 3.9904 | 0.4191 | |
|
| 4.0301 | 3.0 | 2160 | 3.3806 | 0.5032 | |
|
| 3.4797 | 4.0 | 2880 | 2.9065 | 0.5967 | |
|
| 3.0352 | 5.0 | 3600 | 2.5389 | 0.6596 | |
|
| 2.6787 | 6.0 | 4320 | 2.2342 | 0.7044 | |
|
| 2.3644 | 7.0 | 5040 | 1.9873 | 0.7354 | |
|
| 2.1145 | 8.0 | 5760 | 1.7928 | 0.7462 | |
|
| 1.896 | 9.0 | 6480 | 1.6293 | 0.7644 | |
|
| 1.7138 | 10.0 | 7200 | 1.5062 | 0.7752 | |
|
| 1.5625 | 11.0 | 7920 | 1.3923 | 0.7885 | |
|
| 1.4229 | 12.0 | 8640 | 1.3092 | 0.7978 | |
|
| 1.308 | 13.0 | 9360 | 1.2364 | 0.8018 | |
|
| 1.201 | 14.0 | 10080 | 1.1759 | 0.8155 | |
|
| 1.1187 | 15.0 | 10800 | 1.1322 | 0.8214 | |
|
| 1.0384 | 16.0 | 11520 | 1.0990 | 0.8234 | |
|
| 0.976 | 17.0 | 12240 | 1.0615 | 0.8308 | |
|
| 0.9163 | 18.0 | 12960 | 1.0377 | 0.8328 | |
|
| 0.8611 | 19.0 | 13680 | 1.0054 | 0.8337 | |
|
| 0.812 | 20.0 | 14400 | 0.9926 | 0.8367 | |
|
| 0.7721 | 21.0 | 15120 | 0.9712 | 0.8382 | |
|
| 0.7393 | 22.0 | 15840 | 0.9586 | 0.8357 | |
|
| 0.7059 | 23.0 | 16560 | 0.9428 | 0.8372 | |
|
| 0.6741 | 24.0 | 17280 | 0.9377 | 0.8396 | |
|
| 0.6552 | 25.0 | 18000 | 0.9229 | 0.8377 | |
|
| 0.627 | 26.0 | 18720 | 0.9100 | 0.8416 | |
|
| 0.5972 | 27.0 | 19440 | 0.9028 | 0.8416 | |
|
| 0.5784 | 28.0 | 20160 | 0.8996 | 0.8406 | |
|
| 0.5595 | 29.0 | 20880 | 0.8833 | 0.8451 | |
|
| 0.5438 | 30.0 | 21600 | 0.8772 | 0.8475 | |
|
| 0.5218 | 31.0 | 22320 | 0.8758 | 0.8451 | |
|
| 0.509 | 32.0 | 23040 | 0.8728 | 0.8480 | |
|
| 0.4893 | 33.0 | 23760 | 0.8640 | 0.8480 | |
|
| 0.4948 | 34.0 | 24480 | 0.8541 | 0.8475 | |
|
| 0.4722 | 35.0 | 25200 | 0.8595 | 0.8495 | |
|
| 0.468 | 36.0 | 25920 | 0.8488 | 0.8495 | |
|
| 0.4517 | 37.0 | 26640 | 0.8460 | 0.8505 | |
|
| 0.4462 | 38.0 | 27360 | 0.8450 | 0.8485 | |
|
| 0.4396 | 39.0 | 28080 | 0.8422 | 0.8490 | |
|
| 0.427 | 40.0 | 28800 | 0.8380 | 0.8534 | |
|
| 0.4287 | 41.0 | 29520 | 0.8385 | 0.8480 | |
|
| 0.4222 | 42.0 | 30240 | 0.8319 | 0.8510 | |
|
| 0.421 | 43.0 | 30960 | 0.8296 | 0.8510 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.22.1 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.5.1 |
|
- Tokenizers 0.12.1 |
|
|
