metadata
base_model: FacebookAI/roberta-base
library_name: peft
license: mit
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: roberta-base-ner-qlorafinetune-runs-128-256
results: []
roberta-base-ner-qlorafinetune-runs-128-256
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1219
- Precision: 0.9390
- Recall: 0.9644
- F1: 0.9515
- Accuracy: 0.9817
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: 0.0004
- 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: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1187 | 1.0 | 2643 | 0.1579 | 0.9680 | 0.9512 | 0.9595 | 0.9749 |
| 0.1311 | 2.0 | 5286 | 0.1306 | 0.9290 | 0.9607 | 0.9446 | 0.9793 |
| 0.0897 | 3.0 | 7929 | 0.1219 | 0.9390 | 0.9644 | 0.9515 | 0.9817 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1