---
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-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-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: 0.1937
- Accuracy: 0.8562
- Precision: 0.3984
- Recall: 0.5632
- F1: 0.4667

## 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: 3.693911058164899e-06
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3925        | 1.0   | 52   | 0.1759          | 0.8883   | 0.0       | 0.0    | 0.0    |
| 0.3241        | 2.0   | 104  | 0.1606          | 0.8883   | 0.0       | 0.0    | 0.0    |
| 0.2914        | 3.0   | 156  | 0.1744          | 0.8883   | 0.0       | 0.0    | 0.0    |
| 0.2821        | 4.0   | 208  | 0.2609          | 0.8909   | 0.75      | 0.0345 | 0.0659 |
| 0.2739        | 5.0   | 260  | 0.1763          | 0.8935   | 0.75      | 0.0690 | 0.1263 |
| 0.2533        | 6.0   | 312  | 0.1390          | 0.8922   | 0.6154    | 0.0920 | 0.16   |
| 0.2482        | 7.0   | 364  | 0.2199          | 0.8755   | 0.4490    | 0.5057 | 0.4757 |
| 0.2362        | 8.0   | 416  | 0.2124          | 0.8652   | 0.4286    | 0.6207 | 0.5070 |
| 0.2375        | 9.0   | 468  | 0.1351          | 0.8973   | 0.5614    | 0.3678 | 0.4444 |
| 0.228         | 10.0  | 520  | 0.1650          | 0.8870   | 0.4945    | 0.5172 | 0.5056 |
| 0.2212        | 11.0  | 572  | 0.1771          | 0.8845   | 0.4851    | 0.5632 | 0.5213 |
| 0.2217        | 12.0  | 624  | 0.1756          | 0.8832   | 0.4792    | 0.5287 | 0.5027 |
| 0.2109        | 13.0  | 676  | 0.1942          | 0.8614   | 0.4118    | 0.5632 | 0.4757 |
| 0.2018        | 14.0  | 728  | 0.1795          | 0.8678   | 0.4298    | 0.5632 | 0.4876 |
| 0.2013        | 15.0  | 780  | 0.1817          | 0.8652   | 0.4211    | 0.5517 | 0.4776 |
| 0.1943        | 16.0  | 832  | 0.2071          | 0.8575   | 0.4077    | 0.6092 | 0.4885 |
| 0.2023        | 17.0  | 884  | 0.2143          | 0.8498   | 0.3897    | 0.6092 | 0.4753 |
| 0.1924        | 18.0  | 936  | 0.1966          | 0.8562   | 0.4031    | 0.5977 | 0.4815 |
| 0.183         | 19.0  | 988  | 0.1914          | 0.8614   | 0.4118    | 0.5632 | 0.4757 |
| 0.191         | 20.0  | 1040 | 0.1937          | 0.8562   | 0.3984    | 0.5632 | 0.4667 |


### Framework versions

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