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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: depression_classifier_weighted_2
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. -->
# depression_classifier_weighted_2
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0299
- F1: {'f1': 0.5274571619747097}
- Accuracy: {'accuracy': 0.5993836671802774}
## 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: 6
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------:|:--------------------------------:|
| No log | 1.0 | 451 | 0.9802 | {'f1': 0.48800261330578315} | {'accuracy': 0.561171032357473} |
| 0.8742 | 2.0 | 902 | 0.8159 | {'f1': 0.5567921899894229} | {'accuracy': 0.636055469953775} |
| 0.7241 | 3.0 | 1353 | 0.8759 | {'f1': 0.5323551976865734} | {'accuracy': 0.5950693374422188} |
| 0.5999 | 4.0 | 1804 | 1.0016 | {'f1': 0.5186059710481855} | {'accuracy': 0.5685670261941448} |
| 0.465 | 5.0 | 2255 | 1.0535 | {'f1': 0.5143537550061232} | {'accuracy': 0.5722650231124807} |
| 0.3788 | 6.0 | 2706 | 1.0299 | {'f1': 0.5274571619747097} | {'accuracy': 0.5993836671802774} |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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