---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-large-finetuned_ADEs_SonatafyAI
  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-large-finetuned_ADEs_SonatafyAI

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2571
- Precision: 0.5269
- Recall: 0.6208
- F1: 0.5700
- Accuracy: 0.8859

## 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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7192        | 1.0   | 640  | 0.3366          | 0.4491    | 0.5202 | 0.4820 | 0.8653   |
| 0.3549        | 2.0   | 1280 | 0.2814          | 0.4982    | 0.6066 | 0.5471 | 0.8803   |
| 0.3118        | 3.0   | 1920 | 0.2653          | 0.5178    | 0.6186 | 0.5637 | 0.8831   |
| 0.2827        | 4.0   | 2560 | 0.2624          | 0.5276    | 0.6372 | 0.5772 | 0.8833   |
| 0.2741        | 5.0   | 3200 | 0.2571          | 0.5269    | 0.6208 | 0.5700 | 0.8859   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1