---
library_name: transformers
license: apache-2.0
base_model: google/bigbird-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: jackmedda/google-bigbird-roberta-base_finetuned_augmented_augmented_deepseek
  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. -->

# jackmedda/google-bigbird-roberta-base_finetuned_augmented_augmented_deepseek

This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3040
- Accuracy: 0.7647
- F1: 0.8571
- Precision: 0.8
- Recall: 0.9231

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4568        | 1.0   | 46   | 0.7344          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.6053        | 2.0   | 92   | 0.6889          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.5004        | 3.0   | 138  | 0.6289          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.6076        | 4.0   | 184  | 0.6493          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3798        | 5.0   | 230  | 0.7945          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.2401        | 6.0   | 276  | 1.2776          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.4076        | 7.0   | 322  | 1.1325          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.1193        | 8.0   | 368  | 1.1424          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3332        | 9.0   | 414  | 0.9214          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.1445        | 10.0  | 460  | 0.2424          | 0.9      | 0.9333 | 0.875     | 1.0    |
| 0.0029        | 11.0  | 506  | 1.6181          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.1174        | 12.0  | 552  | 0.0031          | 1.0      | 1.0    | 1.0       | 1.0    |
| 0.0014        | 13.0  | 598  | 1.2314          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0011        | 14.0  | 644  | 1.1105          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0008        | 15.0  | 690  | 1.2286          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0008        | 16.0  | 736  | 1.2704          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0006        | 17.0  | 782  | 1.3157          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0005        | 18.0  | 828  | 1.3290          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0005        | 19.0  | 874  | 1.3752          | 0.8      | 0.875  | 0.7778    | 1.0    |
| 0.0004        | 20.0  | 920  | 1.3951          | 0.8      | 0.875  | 0.7778    | 1.0    |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0