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---
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
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