license: apache-2.0 | |
base_model: distilbert/distilbert-base-uncased | |
tags: | |
- generated_from_trainer | |
metrics: | |
- accuracy | |
model-index: | |
- name: Mental_health_identification | |
results: [] | |
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# Mental_health_identification | |
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 0.1649 | |
- Accuracy: 0.9347 | |
## 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: 32 | |
- eval_batch_size: 32 | |
- seed: 42 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: linear | |
- num_epochs: 2 | |
### Training results | |
| Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
|:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| 0.2215 | 1.0 | 1050 | 0.1727 | 0.9260 | | |
| 0.1358 | 2.0 | 2100 | 0.1649 | 0.9347 | | |
### Framework versions | |
- Transformers 4.38.2 | |
- Pytorch 2.1.2 | |
- Datasets 2.1.0 | |
- Tokenizers 0.15.2 | |