metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-base-finetuned-pos
results: []
xlm-roberta-base-finetuned-pos
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0221
- Precision: 0.9948
- Recall: 0.9953
- F1: 0.9951
- Accuracy: 0.9957
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0343 | 1.0 | 2111 | 0.0226 | 0.9941 | 0.9941 | 0.9941 | 0.9949 |
| 0.0205 | 2.0 | 4222 | 0.0230 | 0.9951 | 0.9950 | 0.9951 | 0.9955 |
| 0.0137 | 3.0 | 6333 | 0.0221 | 0.9948 | 0.9953 | 0.9951 | 0.9957 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2