metadata
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: hbertv2-Massive-intent_48_KD
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: 0.8578455484505657
hbertv2-Massive-intent_48_KD
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_48_KD on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.8350
- Accuracy: 0.8578
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 |
|---|---|---|---|---|
| 2.0643 | 1.0 | 180 | 1.1020 | 0.7118 |
| 0.9395 | 2.0 | 360 | 0.8743 | 0.7600 |
| 0.6824 | 3.0 | 540 | 0.7820 | 0.8087 |
| 0.528 | 4.0 | 720 | 0.7761 | 0.8057 |
| 0.4245 | 5.0 | 900 | 0.7209 | 0.8333 |
| 0.3374 | 6.0 | 1080 | 0.7113 | 0.8337 |
| 0.2666 | 7.0 | 1260 | 0.7220 | 0.8362 |
| 0.2107 | 8.0 | 1440 | 0.7670 | 0.8377 |
| 0.1735 | 9.0 | 1620 | 0.7526 | 0.8411 |
| 0.1276 | 10.0 | 1800 | 0.8256 | 0.8465 |
| 0.0984 | 11.0 | 1980 | 0.8074 | 0.8495 |
| 0.0697 | 12.0 | 2160 | 0.7939 | 0.8564 |
| 0.0472 | 13.0 | 2340 | 0.8350 | 0.8578 |
| 0.0292 | 14.0 | 2520 | 0.8511 | 0.8554 |
| 0.018 | 15.0 | 2700 | 0.8536 | 0.8574 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3