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

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: 0.0267
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9886

## 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: 256
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 6    | 0.0868          | 0.0       | 0.0    | 0.0 | 0.9762   |
| No log        | 2.0   | 12   | 0.0533          | 0.0       | 0.0    | 0.0 | 0.9762   |
| No log        | 3.0   | 18   | 0.0303          | 0.0       | 0.0    | 0.0 | 0.9878   |
| No log        | 4.0   | 24   | 0.0267          | 0.0       | 0.0    | 0.0 | 0.9886   |


### Framework versions

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