---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-Validation-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current
  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-Validation-goodareas-eval_FeedbackESConv5pp_CARE10pp-sweeps-current

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3698
- Accuracy: 0.8216
- Precision: 0.4348
- Recall: 0.5932
- F1: 0.5018

## 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: 1.6142257525574262e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4927        | 1.0   | 296  | 0.2877          | 0.8434   | 0.4792    | 0.3898 | 0.4299 |
| 0.3855        | 2.0   | 592  | 0.2566          | 0.8665   | 0.5714    | 0.4746 | 0.5185 |
| 0.3257        | 3.0   | 888  | 0.2534          | 0.8575   | 0.5368    | 0.4322 | 0.4789 |
| 0.2553        | 4.0   | 1184 | 0.3290          | 0.8216   | 0.4371    | 0.6186 | 0.5123 |
| 0.1911        | 5.0   | 1480 | 0.3698          | 0.8216   | 0.4348    | 0.5932 | 0.5018 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0