---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: attr_classification
  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. -->

# attr_classification

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2170
- Precision: 0.9359
- Recall: 0.9574
- F1: 0.9465
- Accuracy: 0.9575

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 139  | 0.2243          | 0.9251    | 0.9311 | 0.9281 | 0.9475   |
| No log        | 2.0   | 278  | 0.2090          | 0.9268    | 0.9541 | 0.9402 | 0.9525   |
| No log        | 3.0   | 417  | 0.2170          | 0.9359    | 0.9574 | 0.9465 | 0.9575   |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1