metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: duraad/nep-spell-mbart-new
model-index:
- name: nep-spell-mbart-new
results: []
nep-spell-mbart-new
This model is a fine-tuned version of duraad/nep-spell-mbart-new on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0020
- Accuracy: 0.7987
- Precision: 0.7987
- Recall: 0.7987
- F1: 0.7987
- Exact Match: 0.7987
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 | Precision | Recall | F1 | Exact Match |
|---|---|---|---|---|---|---|---|---|
| 0.0046 | 0.79 | 1000 | 0.0030 | 0.75 | 0.75 | 0.75 | 0.75 | 0.75 |
| 0.002 | 1.57 | 2000 | 0.0024 | 0.7799 | 0.7799 | 0.7799 | 0.7799 | 0.7799 |
| 0.0008 | 2.36 | 3000 | 0.0020 | 0.7987 | 0.7987 | 0.7987 | 0.7987 | 0.7987 |
Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1