---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: TTC4900Model
  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. -->

# TTC4900Model

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: 3.1884
- Accuracy: 0.6272
- F1: 0.7392
- Precision: 0.7048
- Recall: 0.8129

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.5316        | 0.56  | 50   | 1.1986          | 0.6262   | 0.4825 | 0.5074    | 0.5748 |
| 0.5421        | 1.12  | 100  | 0.2282          | 0.9464   | 0.9318 | 0.9579    | 0.9159 |
| 0.1327        | 1.69  | 150  | 0.2318          | 0.9499   | 0.9542 | 0.9479    | 0.9637 |
| 0.1214        | 2.25  | 200  | 0.1772          | 0.9669   | 0.9688 | 0.9652    | 0.9730 |
| 0.0632        | 2.81  | 250  | 0.2155          | 0.9669   | 0.9688 | 0.9681    | 0.9696 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2