---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-large-finetuned-chunking
  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-finetuned-chunking

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4192
- Precision: 0.3222
- Recall: 0.3161
- F1: 0.3191
- Accuracy: 0.8632

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0373        | 1.0   | 2498  | 0.9545          | 0.3166    | 0.2545 | 0.2822 | 0.8656   |
| 0.0045        | 2.0   | 4996  | 1.1324          | 0.2667    | 0.3142 | 0.2885 | 0.8525   |
| 0.0022        | 3.0   | 7494  | 1.3138          | 0.3349    | 0.3097 | 0.3218 | 0.8672   |
| 0.0015        | 4.0   | 9992  | 1.3454          | 0.3261    | 0.3260 | 0.3260 | 0.8647   |
| 0.0014        | 5.0   | 12490 | 1.3640          | 0.3064    | 0.3126 | 0.3095 | 0.8603   |
| 0.0008        | 6.0   | 14988 | 1.4192          | 0.3222    | 0.3161 | 0.3191 | 0.8632   |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.12.1