---
license: apache-2.0
base_model: bert-large-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-large-uncased-sst-2-64-13-30
  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-large-uncased-sst-2-64-13-30

This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6366
- Accuracy: 0.8594

## 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: 1.5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 4    | 0.6822          | 0.5781   |
| No log        | 2.0   | 8    | 0.6592          | 0.6172   |
| 0.6625        | 3.0   | 12   | 0.6330          | 0.6719   |
| 0.6625        | 4.0   | 16   | 0.5916          | 0.75     |
| 0.5388        | 5.0   | 20   | 0.5256          | 0.8047   |
| 0.5388        | 6.0   | 24   | 0.4758          | 0.8125   |
| 0.5388        | 7.0   | 28   | 0.4535          | 0.8203   |
| 0.3481        | 8.0   | 32   | 0.4449          | 0.8203   |
| 0.3481        | 9.0   | 36   | 0.4246          | 0.8203   |
| 0.2064        | 10.0  | 40   | 0.3979          | 0.8359   |
| 0.2064        | 11.0  | 44   | 0.3869          | 0.8594   |
| 0.2064        | 12.0  | 48   | 0.3902          | 0.8672   |
| 0.1105        | 13.0  | 52   | 0.4068          | 0.8516   |
| 0.1105        | 14.0  | 56   | 0.4299          | 0.8516   |
| 0.0583        | 15.0  | 60   | 0.4556          | 0.8516   |
| 0.0583        | 16.0  | 64   | 0.4352          | 0.8594   |
| 0.0583        | 17.0  | 68   | 0.4515          | 0.8672   |
| 0.0313        | 18.0  | 72   | 0.4882          | 0.8672   |
| 0.0313        | 19.0  | 76   | 0.5242          | 0.8516   |
| 0.0201        | 20.0  | 80   | 0.5497          | 0.8594   |
| 0.0201        | 21.0  | 84   | 0.5667          | 0.8594   |
| 0.0201        | 22.0  | 88   | 0.5827          | 0.8594   |
| 0.0132        | 23.0  | 92   | 0.6062          | 0.8516   |
| 0.0132        | 24.0  | 96   | 0.6265          | 0.8516   |
| 0.017         | 25.0  | 100  | 0.6330          | 0.8438   |
| 0.017         | 26.0  | 104  | 0.6334          | 0.8516   |
| 0.017         | 27.0  | 108  | 0.6354          | 0.8516   |
| 0.0211        | 28.0  | 112  | 0.6361          | 0.8594   |
| 0.0211        | 29.0  | 116  | 0.6363          | 0.8594   |
| 0.0113        | 30.0  | 120  | 0.6366          | 0.8594   |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.4.0
- Tokenizers 0.13.3