---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: boss-sentiment-12000-bert-base-uncased
  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. -->

# boss-sentiment-12000-bert-base-uncased

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- F1: 0.7380
- Acc: 0.8773
- Loss: 0.9558

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | F1     | Acc    | Validation Loss |
|:-------------:|:-----:|:----:|:------:|:------:|:---------------:|
| 0.929         | 1.0   | 750  | 0.6983 | 0.8609 | 0.4073          |
| 0.481         | 2.0   | 1500 | 0.7179 | 0.8689 | 0.3605          |
| 0.3564        | 3.0   | 2250 | 0.7269 | 0.8703 | 0.3834          |
| 0.2369        | 4.0   | 3000 | 0.7006 | 0.8465 | 0.5631          |
| 0.1536        | 5.0   | 3750 | 0.7237 | 0.8591 | 0.6596          |
| 0.1228        | 6.0   | 4500 | 0.7285 | 0.8660 | 0.7316          |
| 0.0831        | 7.0   | 5250 | 0.7454 | 0.8817 | 0.6420          |
| 0.0687        | 8.0   | 6000 | 0.6955 | 0.8354 | 1.1172          |
| 0.0541        | 9.0   | 6750 | 0.7143 | 0.8479 | 1.0556          |
| 0.0465        | 10.0  | 7500 | 0.7473 | 0.8889 | 0.7691          |
| 0.0404        | 11.0  | 8250 | 0.7209 | 0.8636 | 1.0274          |
| 0.0315        | 12.0  | 9000 | 0.7082 | 0.8401 | 1.2706          |
| 0.0329        | 13.0  | 9750 | 0.7380 | 0.8773 | 0.9558          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1