---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: datafun
  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. -->

# datafun

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3032
- Precision: 0.4930
- Recall: 0.5856
- F1: 0.5354
- Accuracy: 0.9049

## 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   | 18   | 0.4004          | 0.4339    | 0.4475 | 0.4406 | 0.8762   |
| No log        | 2.0   | 36   | 0.3122          | 0.4649    | 0.5120 | 0.4873 | 0.9009   |
| No log        | 3.0   | 54   | 0.3032          | 0.4930    | 0.5856 | 0.5354 | 0.9049   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1