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---
license: apache-2.0
base_model: google/bert_uncased_L-2_H-768_A-12
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-2_H-768_A-12_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: 0.8745696015740285
---
<!-- 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_uncased_L-2_H-768_A-12_massive
This model is a fine-tuned version of [google/bert_uncased_L-2_H-768_A-12](https://huggingface.co/google/bert_uncased_L-2_H-768_A-12) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5434
- Accuracy: 0.8746
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5143 | 1.0 | 180 | 1.2564 | 0.7024 |
| 1.0135 | 2.0 | 360 | 0.7279 | 0.8205 |
| 0.6173 | 3.0 | 540 | 0.5817 | 0.8559 |
| 0.433 | 4.0 | 720 | 0.5234 | 0.8598 |
| 0.312 | 5.0 | 900 | 0.5019 | 0.8657 |
| 0.23 | 6.0 | 1080 | 0.5028 | 0.8711 |
| 0.1742 | 7.0 | 1260 | 0.5037 | 0.8682 |
| 0.1314 | 8.0 | 1440 | 0.5018 | 0.8692 |
| 0.1031 | 9.0 | 1620 | 0.5188 | 0.8731 |
| 0.081 | 10.0 | 1800 | 0.5231 | 0.8711 |
| 0.0671 | 11.0 | 1980 | 0.5407 | 0.8716 |
| 0.0569 | 12.0 | 2160 | 0.5309 | 0.8721 |
| 0.0466 | 13.0 | 2340 | 0.5463 | 0.8711 |
| 0.0414 | 14.0 | 2520 | 0.5434 | 0.8746 |
| 0.039 | 15.0 | 2700 | 0.5464 | 0.8721 |
### Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
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