|
|
--- |
|
|
library_name: peft |
|
|
license: mit |
|
|
base_model: xlm-roberta-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
- f1 |
|
|
model-index: |
|
|
- name: emotion-model11_0 |
|
|
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. --> |
|
|
|
|
|
# emotion-model11_0 |
|
|
|
|
|
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.0583 |
|
|
- Accuracy: 0.5828 |
|
|
- F1: 0.5244 |
|
|
|
|
|
## 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: 32 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 10 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
|
| No log | 1.0 | 41 | 1.3349 | 0.3804 | 0.2096 | |
|
|
| 1.3438 | 2.0 | 82 | 1.2443 | 0.3804 | 0.2096 | |
|
|
| 1.2717 | 3.0 | 123 | 1.0583 | 0.5828 | 0.5244 | |
|
|
| 1.1723 | 4.0 | 164 | 1.0449 | 0.5215 | 0.3965 | |
|
|
| 1.1136 | 5.0 | 205 | 0.9935 | 0.5521 | 0.4423 | |
|
|
| 1.1136 | 6.0 | 246 | 0.9746 | 0.5890 | 0.5003 | |
|
|
| 1.1124 | 7.0 | 287 | 0.9637 | 0.5890 | 0.5003 | |
|
|
| 1.0842 | 8.0 | 328 | 0.9562 | 0.5767 | 0.4846 | |
|
|
| 1.0456 | 9.0 | 369 | 0.9516 | 0.5767 | 0.4837 | |
|
|
| 1.0552 | 10.0 | 410 | 0.9428 | 0.5767 | 0.4837 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.15.2 |
|
|
- Transformers 4.52.4 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.6.0 |
|
|
- Tokenizers 0.21.1 |
