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---
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
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