---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ST_DA_100_v2
  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_ST_DA_100_v2

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2371
- Precision: 0.9457
- Recall: 0.9480
- F1: 0.9469
- Accuracy: 0.9446

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 59   | 0.3489          | 0.9065    | 0.9194 | 0.9129 | 0.9085   |
| No log        | 2.0   | 118  | 0.2883          | 0.9190    | 0.9267 | 0.9228 | 0.9180   |
| No log        | 3.0   | 177  | 0.2505          | 0.9322    | 0.9403 | 0.9362 | 0.9330   |
| No log        | 4.0   | 236  | 0.2300          | 0.9384    | 0.9446 | 0.9415 | 0.9384   |
| No log        | 5.0   | 295  | 0.2305          | 0.9397    | 0.9435 | 0.9416 | 0.9386   |
| No log        | 6.0   | 354  | 0.2332          | 0.9443    | 0.9482 | 0.9462 | 0.9438   |
| No log        | 7.0   | 413  | 0.2341          | 0.9433    | 0.9468 | 0.9450 | 0.9429   |
| No log        | 8.0   | 472  | 0.2364          | 0.9441    | 0.9474 | 0.9457 | 0.9430   |
| 0.1814        | 9.0   | 531  | 0.2339          | 0.9457    | 0.9472 | 0.9465 | 0.9439   |
| 0.1814        | 10.0  | 590  | 0.2371          | 0.9457    | 0.9480 | 0.9469 | 0.9446   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1