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---
license: apache-2.0
base_model: google/bert_uncased_L-4_H-256_A-4
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: bert_uncased_L-4_H-256_A-4_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: 0.8362026561731432
---
<!-- 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-4_H-256_A-4_massive
This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7252
- Accuracy: 0.8362
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.5031 | 1.0 | 180 | 2.8542 | 0.4437 |
| 2.5403 | 2.0 | 360 | 2.0782 | 0.6394 |
| 1.928 | 3.0 | 540 | 1.6213 | 0.7118 |
| 1.542 | 4.0 | 720 | 1.3355 | 0.7526 |
| 1.2771 | 5.0 | 900 | 1.1556 | 0.7801 |
| 1.0852 | 6.0 | 1080 | 1.0223 | 0.7964 |
| 0.939 | 7.0 | 1260 | 0.9331 | 0.8047 |
| 0.8352 | 8.0 | 1440 | 0.8670 | 0.8146 |
| 0.7522 | 9.0 | 1620 | 0.8184 | 0.8190 |
| 0.6847 | 10.0 | 1800 | 0.7887 | 0.8254 |
| 0.6369 | 11.0 | 1980 | 0.7578 | 0.8254 |
| 0.5943 | 12.0 | 2160 | 0.7413 | 0.8323 |
| 0.5652 | 13.0 | 2340 | 0.7288 | 0.8328 |
| 0.5486 | 14.0 | 2520 | 0.7252 | 0.8362 |
| 0.5394 | 15.0 | 2700 | 0.7190 | 0.8357 |
### Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
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