metadata
license: mit
base_model: FacebookAI/xlm-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Vic_model
results: []
Vic_model
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3819
- Accuracy: 0.9214
- Precision: 0.9218
- Recall: 0.9214
- F1: 0.9207
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: 5e-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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.7251 | 1.0 | 1225 | 0.5471 | 0.8343 | 0.8489 | 0.8343 | 0.8321 |
| 0.4312 | 2.0 | 2450 | 0.4058 | 0.8986 | 0.9000 | 0.8986 | 0.8974 |
| 0.1904 | 3.0 | 3675 | 0.3819 | 0.9214 | 0.9218 | 0.9214 | 0.9207 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1