license: mit | |
tags: | |
- generated_from_trainer | |
metrics: | |
- accuracy | |
- f1 | |
base_model: xlm-roberta-base | |
model-index: | |
- name: xlm-r-base-leyzer-en-intent | |
results: [] | |
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should probably proofread and complete it, then remove this comment. --> | |
# xlm-r-base-leyzer-en-intent | |
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.1995 | |
- Accuracy: 0.9624 | |
- F1: 0.9624 | |
## 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: 7 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | | |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | |
| 1.9235 | 1.0 | 1061 | 1.5991 | 0.6680 | 0.6680 | | |
| 0.8738 | 2.0 | 2122 | 0.7982 | 0.8359 | 0.8359 | | |
| 0.4406 | 3.0 | 3183 | 0.4689 | 0.9132 | 0.9132 | | |
| 0.2534 | 4.0 | 4244 | 0.3165 | 0.9360 | 0.9360 | | |
| 0.1593 | 5.0 | 5305 | 0.2434 | 0.9507 | 0.9507 | | |
| 0.108 | 6.0 | 6366 | 0.2104 | 0.9599 | 0.9599 | | |
| 0.0914 | 7.0 | 7427 | 0.1995 | 0.9624 | 0.9624 | | |
### Framework versions | |
- Transformers 4.25.1 | |
- Pytorch 1.13.0+cu116 | |
- Datasets 2.8.0 | |
- Tokenizers 0.13.2 | |