|
--- |
|
license: apache-2.0 |
|
base_model: projecte-aina/roberta-base-ca-v2-cased-te |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: 2504v4 |
|
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. --> |
|
|
|
# 2504v4 |
|
|
|
This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6121 |
|
- Accuracy: 0.8193 |
|
- Precision: 0.8296 |
|
- Recall: 0.8193 |
|
- F1: 0.8179 |
|
- Ratio: 0.5882 |
|
|
|
## 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: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.06 |
|
- num_epochs: 4 |
|
- label_smoothing_factor: 0.1 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| |
|
| 2.127 | 0.9870 | 38 | 0.8502 | 0.6345 | 0.6397 | 0.6345 | 0.6310 | 0.5966 | |
|
| 0.7538 | 2.0 | 77 | 0.6640 | 0.7689 | 0.7885 | 0.7689 | 0.7649 | 0.6303 | |
|
| 0.6205 | 2.9870 | 115 | 0.6121 | 0.8193 | 0.8296 | 0.8193 | 0.8179 | 0.5882 | |
|
| 0.5664 | 3.9481 | 152 | 0.6239 | 0.8109 | 0.8278 | 0.8109 | 0.8085 | 0.6134 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
