---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-Reflections-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-Reflections-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: 0.2525
- Accuracy: 0.8947
- Precision: 0.5424
- Recall: 0.3678
- F1: 0.4384

## 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: 3.322508414488167e-05
- train_batch_size: 32
- 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
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.32          | 1.0   | 61   | 0.1403          | 0.8883   | 0.0       | 0.0    | 0.0    |
| 0.2689        | 2.0   | 122  | 0.1174          | 0.8883   | 0.0       | 0.0    | 0.0    |
| 0.2466        | 3.0   | 183  | 0.1255          | 0.8883   | 0.0       | 0.0    | 0.0    |
| 0.2297        | 4.0   | 244  | 0.0992          | 0.8883   | 0.0       | 0.0    | 0.0    |
| 0.2138        | 5.0   | 305  | 0.1326          | 0.8986   | 0.5690    | 0.3793 | 0.4552 |
| 0.1877        | 6.0   | 366  | 0.1163          | 0.8909   | 0.5179    | 0.3333 | 0.4056 |
| 0.1558        | 7.0   | 427  | 0.1209          | 0.8947   | 0.5397    | 0.3908 | 0.4533 |
| 0.135         | 8.0   | 488  | 0.1446          | 0.8896   | 0.5056    | 0.5172 | 0.5114 |
| 0.1208        | 9.0   | 549  | 0.1435          | 0.8986   | 0.5455    | 0.5517 | 0.5486 |
| 0.1212        | 10.0  | 610  | 0.2261          | 0.8665   | 0.4309    | 0.6092 | 0.5048 |
| 0.1011        | 11.0  | 671  | 0.1425          | 0.8973   | 0.5714    | 0.3218 | 0.4118 |
| 0.0918        | 12.0  | 732  | 0.2365          | 0.8832   | 0.4811    | 0.5862 | 0.5285 |
| 0.0892        | 13.0  | 793  | 0.1622          | 0.8935   | 0.525     | 0.4828 | 0.5030 |
| 0.0593        | 14.0  | 854  | 0.1927          | 0.8922   | 0.5273    | 0.3333 | 0.4085 |
| 0.0552        | 15.0  | 915  | 0.3540          | 0.8819   | 0.4762    | 0.5747 | 0.5208 |
| 0.0523        | 16.0  | 976  | 0.2782          | 0.8909   | 0.5119    | 0.4943 | 0.5029 |
| 0.0481        | 17.0  | 1037 | 0.2596          | 0.8922   | 0.5195    | 0.4598 | 0.4878 |
| 0.0435        | 18.0  | 1098 | 0.2729          | 0.8947   | 0.5333    | 0.4598 | 0.4938 |
| 0.0326        | 19.0  | 1159 | 0.2382          | 0.8935   | 0.5385    | 0.3218 | 0.4029 |
| 0.0418        | 20.0  | 1220 | 0.2525          | 0.8947   | 0.5424    | 0.3678 | 0.4384 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.21.0