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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased_fold_3_binary
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_3_binary
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: 1.8310
- F1: 0.7584
## 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 | 289 | 0.4560 | 0.7522 |
| 0.4008 | 2.0 | 578 | 0.4790 | 0.7567 |
| 0.4008 | 3.0 | 867 | 0.6368 | 0.7557 |
| 0.1967 | 4.0 | 1156 | 0.6854 | 0.7534 |
| 0.1967 | 5.0 | 1445 | 0.9823 | 0.7309 |
| 0.0768 | 6.0 | 1734 | 1.2531 | 0.7511 |
| 0.0202 | 7.0 | 2023 | 1.2906 | 0.7391 |
| 0.0202 | 8.0 | 2312 | 1.4025 | 0.7460 |
| 0.0087 | 9.0 | 2601 | 1.5713 | 0.7507 |
| 0.0087 | 10.0 | 2890 | 1.4212 | 0.7528 |
| 0.0162 | 11.0 | 3179 | 1.5775 | 0.7511 |
| 0.0162 | 12.0 | 3468 | 1.6361 | 0.7377 |
| 0.0048 | 13.0 | 3757 | 1.6972 | 0.7542 |
| 0.0098 | 14.0 | 4046 | 1.6569 | 0.7565 |
| 0.0098 | 15.0 | 4335 | 1.7547 | 0.7325 |
| 0.0042 | 16.0 | 4624 | 1.8108 | 0.7544 |
| 0.0042 | 17.0 | 4913 | 1.7593 | 0.7554 |
| 0.0041 | 18.0 | 5202 | 1.7582 | 0.7551 |
| 0.0041 | 19.0 | 5491 | 1.8200 | 0.7512 |
| 0.0029 | 20.0 | 5780 | 1.8310 | 0.7584 |
| 0.0018 | 21.0 | 6069 | 1.8146 | 0.7568 |
| 0.0018 | 22.0 | 6358 | 1.7870 | 0.7558 |
| 0.0029 | 23.0 | 6647 | 1.8508 | 0.7530 |
| 0.0029 | 24.0 | 6936 | 1.8327 | 0.7543 |
| 0.0001 | 25.0 | 7225 | 1.8546 | 0.7561 |
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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