metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: destilbert_uncased_fever_nli
results: []
destilbert_uncased_fever_nli
This model is a fine-tuned version of distilbert-base-uncased on a subset of fever_nli dataset by using the first 7.5k datapoints per each label from the training split. It achieves the following results on the evaluation set:
- Loss: 2.1829
- F1: 0.7045
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- 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 | F1 |
---|---|---|---|---|
No log | 1.0 | 352 | 0.7894 | 0.7029 |
0.5462 | 2.0 | 704 | 0.9908 | 0.7097 |
0.2922 | 3.0 | 1056 | 1.0831 | 0.6924 |
0.2922 | 4.0 | 1408 | 1.2833 | 0.7044 |
0.142 | 5.0 | 1760 | 1.4096 | 0.7008 |
0.0695 | 6.0 | 2112 | 1.5585 | 0.7013 |
0.0695 | 7.0 | 2464 | 1.7262 | 0.7015 |
0.0434 | 8.0 | 2816 | 2.0138 | 0.7016 |
0.0204 | 9.0 | 3168 | 2.0912 | 0.7012 |
0.011 | 10.0 | 3520 | 2.1829 | 0.7045 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2