|
--- |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- recall |
|
- precision |
|
model-index: |
|
- name: mixed_model_combined_data |
|
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. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/yassmenyoussef55-arete-global/huggingface/runs/4lnhrv4o) |
|
# mixed_model_combined_data |
|
|
|
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3112 |
|
- Accuracy: 0.8954 |
|
- F1: 0.8944 |
|
- Recall: 0.8954 |
|
- Precision: 0.8953 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- 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: 0.1 |
|
- training_steps: 849 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
|
| 0.66 | 0.9982 | 212 | 0.7179 | 0.7648 | 0.7546 | 0.7648 | 0.7864 | |
|
| 0.4943 | 1.9965 | 424 | 0.5750 | 0.8136 | 0.8106 | 0.8136 | 0.8352 | |
|
| 0.2822 | 2.9994 | 637 | 0.3672 | 0.8713 | 0.8696 | 0.8713 | 0.8743 | |
|
| 0.1882 | 3.9976 | 849 | 0.3112 | 0.8954 | 0.8944 | 0.8954 | 0.8953 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
