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

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0016
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9997

## 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-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 0.0143        | 1.0   | 938  | 0.0032          | 0.0       | 0.0    | 0.0 | 0.9995   |
| 0.0033        | 2.0   | 1876 | 0.0017          | 0.0       | 0.0    | 0.0 | 0.9996   |
| 0.0039        | 3.0   | 2814 | 0.0018          | 0.0       | 0.0    | 0.0 | 0.9997   |
| 0.0012        | 4.0   | 3752 | 0.0016          | 0.0       | 0.0    | 0.0 | 0.9997   |


### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.10.1
- Datasets 2.6.1
- Tokenizers 0.13.1