siddharthgowda/NOT-SCALLING-finetuned-roBERTa-tweet-virality-predictor-classifcation-head-step
8719aec
verified
metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: >-
NOT-SCALLING-finetuned-roBERTa-tweet-virality-predictor-classifcation-head-step
results: []
NOT-SCALLING-finetuned-roBERTa-tweet-virality-predictor-classifcation-head-step
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3192
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: 1e-05
- train_batch_size: 128
- eval_batch_size: 8
- seed: 42
- 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: 0.06
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3505 | 1.0 | 730 | 0.3343 |
| 0.3243 | 2.0 | 1460 | 0.3249 |
| 0.3223 | 3.0 | 2190 | 0.3207 |
| 0.3201 | 4.0 | 2920 | 0.3197 |
| 0.324 | 5.0 | 3650 | 0.3192 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1