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---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: fintunned-v2-roberta_GA
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. -->
# fintunned-v2-roberta_GA
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1635
- Accuracy: 0.9523
- F1: 0.9527
- Precision: 0.9534
- Recall: 0.9523
## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 2.3896 | 0.45 | 50 | 2.2632 | 0.325 | 0.2696 | 0.4504 | 0.3447 |
| 1.2481 | 0.91 | 100 | 0.4536 | 0.8841 | 0.8873 | 0.8940 | 0.8892 |
| 0.3487 | 1.36 | 150 | 0.2978 | 0.9136 | 0.9161 | 0.9186 | 0.9167 |
| 0.2618 | 1.82 | 200 | 0.2472 | 0.9295 | 0.9319 | 0.9362 | 0.9313 |
| 0.2223 | 2.27 | 250 | 0.1872 | 0.9409 | 0.9415 | 0.9445 | 0.9408 |
| 0.076 | 2.73 | 300 | 0.1635 | 0.9523 | 0.9527 | 0.9534 | 0.9523 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
|