---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: bert-base-phia-secondhandDescription-1000
  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-phia-secondhandDescription-1000

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9318
- Precision: 0.8414
- Recall: 0.8311
- Accuracy: 0.8311
- F1: 0.8306

## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
| No log        | 1.0   | 84   | 1.4608          | 0.7781    | 0.6824 | 0.6824   | 0.6766 |
| No log        | 2.0   | 168  | 0.7149          | 0.8298    | 0.8176 | 0.8176   | 0.8185 |
| 1.4174        | 3.0   | 252  | 0.6704          | 0.8229    | 0.8041 | 0.8041   | 0.8036 |
| 1.4174        | 4.0   | 336  | 0.8298          | 0.8359    | 0.7973 | 0.7973   | 0.7974 |
| 0.2952        | 5.0   | 420  | 0.7800          | 0.8525    | 0.8311 | 0.8311   | 0.8305 |
| 0.2952        | 6.0   | 504  | 0.8365          | 0.8464    | 0.8311 | 0.8311   | 0.8312 |
| 0.2952        | 7.0   | 588  | 0.9032          | 0.8309    | 0.8176 | 0.8176   | 0.8184 |
| 0.0537        | 8.0   | 672  | 0.8952          | 0.8337    | 0.8243 | 0.8243   | 0.8237 |
| 0.0537        | 9.0   | 756  | 0.9206          | 0.8414    | 0.8311 | 0.8311   | 0.8306 |
| 0.0243        | 10.0  | 840  | 0.9318          | 0.8414    | 0.8311 | 0.8311   | 0.8306 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1