peft safetensors generated_from_trainer base_model:roberta-large license:mit region:us
---
license: mit
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: roberta-large
model-index:
- name: roberta-large-finetuned-ner
  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-ner

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: 0.0828
- Precision: 0.9043
- Recall: 0.9245
- F1: 0.9143
- Accuracy: 0.9793

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.8259        | 1.0   | 878  | 0.2398          | 0.6827    | 0.7083 | 0.6953 | 0.9371   |
| 0.2115        | 2.0   | 1756 | 0.1560          | 0.8021    | 0.8172 | 0.8096 | 0.9600   |
| 0.1612        | 3.0   | 2634 | 0.1274          | 0.8589    | 0.8506 | 0.8547 | 0.9672   |
| 0.124         | 4.0   | 3512 | 0.1081          | 0.8832    | 0.8793 | 0.8813 | 0.9722   |
| 0.1183        | 5.0   | 4390 | 0.0993          | 0.8910    | 0.9036 | 0.8973 | 0.9754   |
| 0.1074        | 6.0   | 5268 | 0.0921          | 0.8974    | 0.9119 | 0.9046 | 0.9773   |
| 0.1004        | 7.0   | 6146 | 0.0874          | 0.8983    | 0.9156 | 0.9068 | 0.9780   |
| 0.0967        | 8.0   | 7024 | 0.0846          | 0.9028    | 0.9227 | 0.9127 | 0.9792   |
| 0.0923        | 9.0   | 7902 | 0.0829          | 0.9039    | 0.9239 | 0.9138 | 0.9795   |
| 0.0884        | 10.0  | 8780 | 0.0828          | 0.9043    | 0.9245 | 0.9143 | 0.9793   |


### Framework versions

- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.17.0
- Tokenizers 0.15.2