---
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: 0.7517
- Accuracy: 0.8331
- Precision: 0.4610
- Recall: 0.6017
- F1: 0.5221

## 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: 3.263554762497362e-06
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.533         | 1.0   | 486  | 0.3998          | 0.8485   | 0.0       | 0.0    | 0.0    |
| 0.4106        | 2.0   | 972  | 0.3184          | 0.8601   | 0.5714    | 0.3051 | 0.3978 |
| 0.3506        | 3.0   | 1458 | 0.3458          | 0.8665   | 0.5778    | 0.4407 | 0.5    |
| 0.3103        | 4.0   | 1944 | 0.3449          | 0.8460   | 0.4926    | 0.5678 | 0.5276 |
| 0.2684        | 5.0   | 2430 | 0.3504          | 0.8472   | 0.4959    | 0.5085 | 0.5021 |
| 0.2295        | 6.0   | 2916 | 0.4242          | 0.8588   | 0.5299    | 0.6017 | 0.5635 |
| 0.1905        | 7.0   | 3402 | 0.5236          | 0.8549   | 0.5191    | 0.5763 | 0.5462 |
| 0.1614        | 8.0   | 3888 | 0.6659          | 0.8434   | 0.4859    | 0.5847 | 0.5308 |
| 0.1499        | 9.0   | 4374 | 0.7185          | 0.8421   | 0.4825    | 0.5847 | 0.5287 |
| 0.1347        | 10.0  | 4860 | 0.7517          | 0.8331   | 0.4610    | 0.6017 | 0.5221 |


### Framework versions

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