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---
base_model: FacebookAI/roberta-base
library_name: peft
license: mit
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: roberta-base-ner-qlorafinetune-runs-32-64
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. -->
# roberta-base-ner-qlorafinetune-runs-32-64
This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1135
- Precision: 0.9482
- Recall: 0.9690
- F1: 0.9585
- Accuracy: 0.9845
## 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: 0.0004
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1109 | 1.0 | 2643 | 0.1480 | 0.9267 | 0.9538 | 0.9401 | 0.9759 |
| 0.1136 | 2.0 | 5286 | 0.1192 | 0.9383 | 0.9645 | 0.9512 | 0.9818 |
| 0.0832 | 3.0 | 7929 | 0.1135 | 0.9482 | 0.9690 | 0.9585 | 0.9845 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |