|
--- |
|
license: mit |
|
base_model: FacebookAI/xlm-roberta-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- precision |
|
- recall |
|
model-index: |
|
- name: training_dir |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# training_dir |
|
|
|
This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4296 |
|
- Accuracy: 0.8650 |
|
- F1: 0.8647 |
|
- Precision: 0.8662 |
|
- Recall: 0.8650 |
|
- Accuracy Label Communication Issue: 0.3878 |
|
- Accuracy Label General Query: 0.5135 |
|
- Accuracy Label Other: 0.8535 |
|
- Accuracy Label Praise: 0.7987 |
|
- Accuracy Label Service Issue: 0.9503 |
|
|
|
## 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: 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 | Accuracy | F1 | Precision | Recall | Accuracy Label Communication Issue | Accuracy Label General Query | Accuracy Label Other | Accuracy Label Praise | Accuracy Label Service Issue | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:----------------------------------:|:----------------------------:|:--------------------:|:---------------------:|:----------------------------:| |
|
| 0.4926 | 1.0 | 220 | 0.4769 | 0.8351 | 0.7977 | 0.7654 | 0.8351 | 0.0 | 0.0 | 0.8479 | 0.7315 | 0.9780 | |
|
| 0.4722 | 2.0 | 440 | 0.4490 | 0.8138 | 0.8335 | 0.8685 | 0.8138 | 0.5918 | 0.2973 | 0.8592 | 0.8523 | 0.8358 | |
|
| 0.1949 | 3.0 | 660 | 0.4296 | 0.8650 | 0.8647 | 0.8662 | 0.8650 | 0.3878 | 0.5135 | 0.8535 | 0.7987 | 0.9503 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
