metadata
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: fine-tuned-NLI-mnli_original-with-roberta-large
results: []
fine-tuned-NLI-mnli_original-with-roberta-large
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3381
- Accuracy: 0.9053
- F1: 0.9056
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.3302 | 0.4997 | 1533 | 0.2972 | 0.8940 | 0.8934 |
| 0.3139 | 0.9993 | 3066 | 0.2751 | 0.9027 | 0.9030 |
| 0.242 | 1.4990 | 4599 | 0.2866 | 0.9030 | 0.9030 |
| 0.2627 | 1.9987 | 6132 | 0.2921 | 0.9065 | 0.9066 |
| 0.1818 | 2.4984 | 7665 | 0.3049 | 0.9035 | 0.9038 |
| 0.1932 | 2.9980 | 9198 | 0.3153 | 0.9039 | 0.9038 |
| 0.1457 | 3.4977 | 10731 | 0.3381 | 0.9053 | 0.9056 |
Framework versions
- Transformers 4.42.3
- Pytorch 1.13.1+cu117
- Datasets 2.2.0
- Tokenizers 0.19.1