---
library_name: transformers
license: mit
base_model: adity12345/RoBerta_Medhhml
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Roberta_reddit
  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_reddit

This model is a fine-tuned version of [adity12345/RoBerta_Medhhml](https://huggingface.co/adity12345/RoBerta_Medhhml) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Accuracy: 1.0
- Auc: nan
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- F1-macro: 1.0
- F1-micro: 1.0
- F1-weighted: 1.0

## 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: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc | Precision | Recall | F1  | F1-macro | F1-micro | F1-weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|:---:|:--------:|:--------:|:-----------:|
| 0.004         | 2.0   | 50   | 0.0003          | 1.0      | nan | 0.0       | 0.0    | 0.0 | 1.0      | 1.0      | 1.0         |


### Framework versions

- Transformers 4.55.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4