---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_base_96
  results: []
---

<!-- 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_base_96

This model is a fine-tuned version of [gokuls/bert_base_48](https://huggingface.co/gokuls/bert_base_48) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6333
- Accuracy: 0.5281

## 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: 1e-05
- train_batch_size: 48
- eval_batch_size: 48
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 5.6041        | 0.08  | 10000  | 5.5567          | 0.1751   |
| 5.4727        | 0.16  | 20000  | 5.3950          | 0.1953   |
| 5.3385        | 0.25  | 30000  | 5.2277          | 0.2151   |
| 5.2033        | 0.33  | 40000  | 5.0607          | 0.2335   |
| 4.7807        | 0.41  | 50000  | 4.5611          | 0.2910   |
| 4.1994        | 0.49  | 60000  | 4.0039          | 0.3520   |
| 3.8039        | 0.57  | 70000  | 3.6509          | 0.3906   |
| 3.5516        | 0.66  | 80000  | 3.3794          | 0.4263   |
| 3.3199        | 0.74  | 90000  | 3.1446          | 0.4607   |
| 3.1682        | 0.82  | 100000 | 3.0053          | 0.4795   |
| 3.0597        | 0.9   | 110000 | 2.9135          | 0.4919   |
| 2.9814        | 0.98  | 120000 | 2.8331          | 0.5018   |
| 2.907         | 1.07  | 130000 | 2.7724          | 0.5100   |
| 2.8532        | 1.15  | 140000 | 2.7200          | 0.5170   |
| 2.8044        | 1.23  | 150000 | 2.6759          | 0.5227   |
| 2.7694        | 1.31  | 160000 | 2.6333          | 0.5281   |


### Framework versions

- Transformers 4.30.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3