Downloads · 30 days
5
19% of all-time downloads
mca-sentiment-analyzer-v2
Relacosm/mca-sentiment-analyzer-v2
mca-sentiment-analyzer-v2 is a text classification model from Relacosm. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as cc-by-4.0.
should probably proofread and complete it, then remove this comment. --
All-time downloads
26
Public
Parameters
125M
7.5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors499 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- cc-by-4.0
- Model type
- roberta
- Access
- Public
- Created
- Aug 31, 2025
- Updated
- Sep 26, 2025
- SHA
- b59e51e1
Try a prompt
Base models
Spaces
Model card
From the Hugging Face model README
<!-- 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. -->
mca-sentiment-analyzer-v2
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment-latest on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1090
- Accuracy: 0.9668
- F1 Macro: 0.9673
- F1 Weighted: 0.9669
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
|---|---|---|---|---|---|---|
| 1.2893 | 0.1559 | 20 | 0.9350 | 0.6074 | 0.4810 | 0.4802 |
| 0.8368 | 0.3119 | 40 | 0.5051 | 0.8848 | 0.8833 | 0.8831 |
| 0.6255 | 0.4678 | 60 | 0.2471 | 0.9336 | 0.9341 | 0.9336 |
| 0.469 | 0.6238 | 80 | 0.1967 | 0.9297 | 0.9299 | 0.9295 |
| 0.3423 | 0.7797 | 100 | 0.1227 | 0.9551 | 0.9558 | 0.9553 |
| 0.3477 | 0.9357 | 120 | 0.1090 | 0.9668 | 0.9673 | 0.9669 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- cc-by-4.0
- Created
- Aug 31, 2025
- Updated
- Sep 26, 2025