---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: BERT-Base-emotion-no-love-v0.1
  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-emotion-no-love-v0.1

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: 4.1705
- Accuracy: 0.4259
- F1: 0.4219

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 167  | 2.1204          | 0.4221   | 0.4247 |
| No log        | 2.0   | 334  | 3.0131          | 0.4198   | 0.4240 |
| 0.393         | 3.0   | 501  | 3.4429          | 0.4174   | 0.4159 |
| 0.393         | 4.0   | 668  | 3.7513          | 0.4228   | 0.4140 |
| 0.393         | 5.0   | 835  | 3.9349          | 0.4298   | 0.4251 |
| 0.0602        | 6.0   | 1002 | 4.0416          | 0.4213   | 0.4189 |
| 0.0602        | 7.0   | 1169 | 4.1247          | 0.4221   | 0.4195 |
| 0.0602        | 8.0   | 1336 | 4.1705          | 0.4259   | 0.4219 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1