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license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased_fold_7_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_7_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: 1.8361
- F1: 0.7958
## 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 | 0.4025 | 0.8071 |
| 0.3986 | 2.0 | 576 | 0.3979 | 0.8072 |
| 0.3986 | 3.0 | 864 | 0.5170 | 0.8041 |
| 0.1761 | 4.0 | 1152 | 0.7946 | 0.7940 |
| 0.1761 | 5.0 | 1440 | 1.0000 | 0.7937 |
| 0.0705 | 6.0 | 1728 | 1.1484 | 0.7875 |
| 0.0294 | 7.0 | 2016 | 1.1548 | 0.8042 |
| 0.0294 | 8.0 | 2304 | 1.3036 | 0.8069 |
| 0.0171 | 9.0 | 2592 | 1.4043 | 0.7943 |
| 0.0171 | 10.0 | 2880 | 1.3356 | 0.8002 |
| 0.0154 | 11.0 | 3168 | 1.4528 | 0.7996 |
| 0.0154 | 12.0 | 3456 | 1.5514 | 0.7991 |
| 0.005 | 13.0 | 3744 | 1.6341 | 0.8046 |
| 0.0038 | 14.0 | 4032 | 1.6240 | 0.7984 |
| 0.0038 | 15.0 | 4320 | 1.7476 | 0.8014 |
| 0.0037 | 16.0 | 4608 | 1.6666 | 0.7982 |
| 0.0037 | 17.0 | 4896 | 1.7495 | 0.7950 |
| 0.0083 | 18.0 | 5184 | 1.6993 | 0.7932 |
| 0.0083 | 19.0 | 5472 | 1.6573 | 0.8077 |
| 0.002 | 20.0 | 5760 | 1.7430 | 0.7980 |
| 0.0012 | 21.0 | 6048 | 1.8135 | 0.7955 |
| 0.0012 | 22.0 | 6336 | 1.8316 | 0.7972 |
| 0.0022 | 23.0 | 6624 | 1.8717 | 0.7926 |
| 0.0022 | 24.0 | 6912 | 1.8183 | 0.7978 |
| 0.0014 | 25.0 | 7200 | 1.8361 | 0.7958 |
### Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
|