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---
license: apache-2.0
base_model: distilroberta-base
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa_conll_learning_rate7e5
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: conll2003
type: conll2003
config: conll2003
split: validation
args: conll2003
metrics:
- name: Precision
type: precision
value: 0.9373342175066313
- name: Recall
type: recall
value: 0.9515314708852238
- name: F1
type: f1
value: 0.9443794888926006
- name: Accuracy
type: accuracy
value: 0.9872203982694608
---
<!-- 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_conll_learning_rate7e5
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0592
- Precision: 0.9373
- Recall: 0.9515
- F1: 0.9444
- Accuracy: 0.9872
## 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: 7e-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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0822 | 1.0 | 1756 | 0.0665 | 0.9087 | 0.9349 | 0.9216 | 0.9821 |
| 0.0329 | 2.0 | 3512 | 0.0644 | 0.9340 | 0.9429 | 0.9384 | 0.9860 |
| 0.0205 | 3.0 | 5268 | 0.0592 | 0.9373 | 0.9515 | 0.9444 | 0.9872 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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