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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased_fold_1_binary_v1
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# distilbert-base-uncased_fold_1_binary_v1
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7296
- F1: 0.8038
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 288 | 0.4152 | 0.7903 |
| 0.3956 | 2.0 | 576 | 0.4037 | 0.8083 |
| 0.3956 | 3.0 | 864 | 0.5601 | 0.7996 |
| 0.181 | 4.0 | 1152 | 0.8571 | 0.8023 |
| 0.181 | 5.0 | 1440 | 0.9704 | 0.7822 |
| 0.0935 | 6.0 | 1728 | 0.9509 | 0.8074 |
| 0.0418 | 7.0 | 2016 | 1.1813 | 0.7736 |
| 0.0418 | 8.0 | 2304 | 1.2619 | 0.7859 |
| 0.0134 | 9.0 | 2592 | 1.4275 | 0.7863 |
| 0.0134 | 10.0 | 2880 | 1.4035 | 0.8019 |
| 0.0127 | 11.0 | 3168 | 1.4903 | 0.7897 |
| 0.0127 | 12.0 | 3456 | 1.5853 | 0.7919 |
| 0.0061 | 13.0 | 3744 | 1.6628 | 0.7957 |
| 0.0058 | 14.0 | 4032 | 1.5736 | 0.8060 |
| 0.0058 | 15.0 | 4320 | 1.6226 | 0.7929 |
| 0.0065 | 16.0 | 4608 | 1.6395 | 0.8010 |
| 0.0065 | 17.0 | 4896 | 1.6556 | 0.7993 |
| 0.002 | 18.0 | 5184 | 1.7075 | 0.8030 |
| 0.002 | 19.0 | 5472 | 1.6925 | 0.7964 |
| 0.0058 | 20.0 | 5760 | 1.6511 | 0.8030 |
| 0.0013 | 21.0 | 6048 | 1.6135 | 0.8037 |
| 0.0013 | 22.0 | 6336 | 1.6739 | 0.8028 |
| 0.0001 | 23.0 | 6624 | 1.7014 | 0.8109 |
| 0.0001 | 24.0 | 6912 | 1.7015 | 0.8045 |
| 0.002 | 25.0 | 7200 | 1.7296 | 0.8038 |
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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