metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: xlm-r-base-amazon-massive-intent
results: []
xlm-r-base-amazon-massive-intent
This model is a fine-tuned version of xlm-roberta-base on Amazon Massive dataset (only en-US subset). It achieves the following results on the evaluation set:
- Loss: 0.5439
- Accuracy: 0.8775
- F1: 0.8775
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 2.734 | 1.0 | 720 | 1.1883 | 0.7196 | 0.7196 |
| 1.2774 | 2.0 | 1440 | 0.7162 | 0.8342 | 0.8342 |
| 0.6301 | 3.0 | 2160 | 0.5817 | 0.8672 | 0.8672 |
| 0.4901 | 4.0 | 2880 | 0.5555 | 0.8770 | 0.8770 |
| 0.3398 | 5.0 | 3600 | 0.5439 | 0.8775 | 0.8775 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1