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

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0410
- Accuracy: 0.6019
- Precision: 0.6044
- Recall: 0.6019
- F1: 0.6029

## 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: 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: 100
- num_epochs: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2489        | 1.0   | 78   | 1.2061          | 0.4790   | 0.3740    | 0.4790 | 0.3999 |
| 1.0356        | 2.0   | 156  | 1.0236          | 0.6019   | 0.6244    | 0.6019 | 0.5841 |
| 0.8625        | 3.0   | 234  | 0.9983          | 0.6181   | 0.6274    | 0.6181 | 0.6126 |
| 0.7101        | 4.0   | 312  | 0.9687          | 0.6019   | 0.6004    | 0.6019 | 0.5998 |
| 0.5945        | 5.0   | 390  | 0.9962          | 0.6181   | 0.6178    | 0.6181 | 0.6157 |
| 0.4753        | 6.0   | 468  | 1.0245          | 0.6246   | 0.6337    | 0.6246 | 0.6256 |
| 0.3903        | 7.0   | 546  | 1.0410          | 0.6019   | 0.6044    | 0.6019 | 0.6029 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0