metadata
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
datasets:
- cosmos_qa
metrics:
- accuracy
model-index:
- name: roberta-large-finetuned-cosmos
results: []
roberta-large-finetuned-cosmos
This model is a fine-tuned version of roberta-large on the cosmos_qa dataset. It achieves the following results on the evaluation set:
- Loss: 1.3863
- Accuracy: 0.2533
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.39 | 1.0 | 12631 | 1.3863 | 0.2586 |
| 1.3956 | 2.0 | 25262 | 1.3863 | 0.2563 |
| 1.3902 | 3.0 | 37893 | 1.3863 | 0.2533 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2