|
--- |
|
base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: sentiment_analysis_model_rpsi |
|
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/themohal/huggingface/runs/ddp65niu) |
|
# sentiment_analysis_model_rpsi |
|
|
|
This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual](https://huggingface.co./cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5686 |
|
- Accuracy: 0.8018 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 6 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.7314 | 1.0 | 3378 | 0.6028 | 0.7367 | |
|
| 0.563 | 2.0 | 6756 | 0.5503 | 0.7646 | |
|
| 0.4859 | 3.0 | 10134 | 0.5316 | 0.7847 | |
|
| 0.421 | 4.0 | 13512 | 0.5223 | 0.7954 | |
|
| 0.3668 | 5.0 | 16890 | 0.5514 | 0.7973 | |
|
| 0.3266 | 6.0 | 20268 | 0.5686 | 0.8018 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.3 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
