---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: roberta-base-finetuned-squad-v2
  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-finetuned-squad-v2

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8475

{"exact": 78.50585361745136,
"f1": 81.58359022842608, 
"total": 11873, 
"HasAns_exact": 77.71592442645074, 
"HasAns_f1": 83.8802238161443, 
"HasAns_total": 5928, 
"NoAns_exact": 79.29352396972246, 
"NoAns_f1": 79.29352396972246, 
"NoAns_total": 5945, 
"best_exact": 79.41548050197927, 
"best_exact_thresh": 0.17161580696895154, 
"best_f1": 82.14757970157191, 
"best_f1_thresh": 0.17426970650172677, 
"pr_exact_ap": 65.90521604124024, 
"pr_f1_ap": 75.35707443729065, 
"pr_oracle_ap": 91.89035655865922}

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9481        | 0.9996 | 2059 | 0.8358          |
| 0.7421        | 1.9998 | 4119 | 0.8362          |
| 0.6294        | 2.9989 | 6177 | 0.8475          |


### Framework versions

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