---
license: apache-2.0
base_model: retrieva-jp/bert-1.3b
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: out
  results: []
---

# retriva-bert-preference-classifier

This model is a fine-tuned version of [retrieva-jp/bert-1.3b](https://huggingface.co/retrieva-jp/bert-1.3b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4714
- Accuracy: 0.737
- Precision: 0.7423
- Recall: 0.726
- F1: 0.7341

## 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: 5e-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
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6438        | 0.0080 | 100  | 0.6116          | 0.663    | 0.8721    | 0.382  | 0.5313 |
| 0.5113        | 0.0160 | 200  | 0.5442          | 0.699    | 0.6736    | 0.772  | 0.7195 |
| 0.4512        | 0.0240 | 300  | 0.5119          | 0.717    | 0.8359    | 0.54   | 0.6561 |
| 0.3916        | 0.0321 | 400  | 0.4936          | 0.702    | 0.7295    | 0.642  | 0.6830 |
| 0.3806        | 0.0401 | 500  | 0.4763          | 0.715    | 0.7708    | 0.612  | 0.6823 |
| 0.3581        | 0.0481 | 600  | 0.4597          | 0.754    | 0.75      | 0.762  | 0.7560 |
| 0.3308        | 0.0561 | 700  | 0.4690          | 0.742    | 0.7738    | 0.684  | 0.7261 |
| 0.3458        | 0.0641 | 800  | 0.4703          | 0.737    | 0.7423    | 0.726  | 0.7341 |
| 0.3475        | 0.0721 | 900  | 0.4728          | 0.737    | 0.7495    | 0.712  | 0.7303 |
| 0.3435        | 0.0801 | 1000 | 0.4714          | 0.737    | 0.7423    | 0.726  | 0.7341 |

### Evaluation on test split

![image/png](https://cdn-uploads.huggingface.co/production/uploads/651e3f30ca333f3c8df692b8/9lbpMeSt30w_KSd4hZKxe.png)

### Framework versions

- Transformers 4.43.1
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1