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---
license: mit
base_model: LIAMF-USP/roberta-large-finetuned-race
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-mqa-formrat
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-mqa-formrat
This model is a fine-tuned version of [LIAMF-USP/roberta-large-finetuned-race](https://huggingface.co./LIAMF-USP/roberta-large-finetuned-race) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6094
- Accuracy: 0.2075
- F1: 0.1943
- Precision: 0.2025
- Recall: 0.2019
## 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: 16
- seed: 42
- 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 | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.6083 | 1.0 | 3712 | 1.6094 | 0.1981 | 0.1925 | 0.1939 | 0.1944 |
| 1.6124 | 2.0 | 7424 | 1.6094 | 0.2050 | 0.2020 | 0.2033 | 0.2030 |
| 1.6113 | 3.0 | 11136 | 1.6094 | 0.2075 | 0.1943 | 0.2025 | 0.2019 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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