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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased-text-classification-v6
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-text-classification-v6
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: 0.2704
- F1: 0.8474
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.3969 | 1.0 | 569 | 0.6767 | 0.4906 |
| 0.6361 | 2.0 | 1138 | 0.4067 | 0.7038 |
| 0.3966 | 3.0 | 1707 | 0.3094 | 0.7988 |
| 0.2509 | 4.0 | 2276 | 0.2744 | 0.8339 |
| 0.1678 | 5.0 | 2845 | 0.2704 | 0.8474 |
| 0.126 | 6.0 | 3414 | 0.2810 | 0.8530 |
| 0.098 | 7.0 | 3983 | 0.3025 | 0.8582 |
| 0.0722 | 8.0 | 4552 | 0.2982 | 0.8556 |
| 0.0631 | 9.0 | 5121 | 0.3026 | 0.8597 |
| 0.0581 | 10.0 | 5690 | 0.3059 | 0.8614 |
| 0.0615 | 11.0 | 6259 | 0.3016 | 0.8623 |
| 0.0567 | 12.0 | 6828 | 0.3108 | 0.8608 |
| 0.0572 | 13.0 | 7397 | 0.3072 | 0.8577 |
| 0.0469 | 14.0 | 7966 | 0.3147 | 0.8563 |
| 0.0493 | 15.0 | 8535 | 0.3229 | 0.8637 |
| 0.0477 | 16.0 | 9104 | 0.3183 | 0.8705 |
| 0.0482 | 17.0 | 9673 | 0.3212 | 0.8676 |
| 0.0442 | 18.0 | 10242 | 0.3193 | 0.8667 |
| 0.0432 | 19.0 | 10811 | 0.3224 | 0.8665 |
| 0.0409 | 20.0 | 11380 | 0.3220 | 0.8663 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3
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