metadata
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
model-index:
- name: roberta_cosine_adamw_torch_fused
results: []
roberta_cosine_adamw_torch_fused
This model is a fine-tuned version of FacebookAI/roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4842
- F1 macro: 0.2732
- Weighted: 0.4704
- Balanced accuracy: 0.3585
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 macro | Weighted | Balanced accuracy |
|---|---|---|---|---|---|---|
| 1.936 | 1.0 | 77 | 1.9420 | 0.0143 | 0.0070 | 0.125 |
| 1.747 | 2.0 | 154 | 1.7184 | 0.1319 | 0.2747 | 0.2271 |
| 1.6439 | 3.0 | 231 | 1.7182 | 0.1717 | 0.2495 | 0.2961 |
| 1.5361 | 4.0 | 308 | 1.4554 | 0.2328 | 0.4842 | 0.3004 |
| 1.3294 | 5.0 | 385 | 1.5815 | 0.2189 | 0.3779 | 0.3188 |
| 1.1602 | 6.0 | 462 | 1.5172 | 0.2386 | 0.4371 | 0.3296 |
| 1.2601 | 7.0 | 539 | 1.4842 | 0.2732 | 0.4704 | 0.3585 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1