---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: e_care_bert_base_uncased_finetuned
  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. -->

# e_care_bert_base_uncased_finetuned

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: 0.7829
- F1: 0.7700

## 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: 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: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5606        | 1.0   | 933  | 0.4842          | 0.7568 |
| 0.3887        | 2.0   | 1866 | 0.5027          | 0.7630 |
| 0.2741        | 3.0   | 2799 | 0.6025          | 0.7625 |
| 0.1878        | 4.0   | 3732 | 0.7185          | 0.7714 |
| 0.1404        | 5.0   | 4665 | 0.7668          | 0.7667 |
| 0.1202        | 6.0   | 5598 | 0.7829          | 0.7700 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1