---
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-100
  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-100

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: 2.2601
- Precision: 0.3167
- Recall: 0.3333
- Accuracy: 0.3333
- F1: 0.2933

## 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   | 9    | 2.4405          | 0.0       | 0.0    | 0.0      | 0.0    |
| No log        | 2.0   | 18   | 2.3760          | 0.0833    | 0.2    | 0.2      | 0.1156 |
| No log        | 3.0   | 27   | 2.3655          | 0.0148    | 0.0667 | 0.0667   | 0.0242 |
| No log        | 4.0   | 36   | 2.4138          | 0.0467    | 0.1333 | 0.1333   | 0.0667 |
| No log        | 5.0   | 45   | 2.3539          | 0.2833    | 0.3333 | 0.3333   | 0.2933 |
| No log        | 6.0   | 54   | 2.3328          | 0.075     | 0.1333 | 0.1333   | 0.0815 |
| No log        | 7.0   | 63   | 2.3062          | 0.1095    | 0.2    | 0.2      | 0.1278 |
| No log        | 8.0   | 72   | 2.3072          | 0.3111    | 0.3333 | 0.3333   | 0.2857 |
| No log        | 9.0   | 81   | 2.2739          | 0.2611    | 0.3333 | 0.3333   | 0.2800 |
| No log        | 10.0  | 90   | 2.2601          | 0.3167    | 0.3333 | 0.3333   | 0.2933 |


### Framework versions

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