transformers pytorch bert text-classification generated_from_trainer dataset:shc_deva_ds model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- shc_deva_ds
metrics:
- f1
tags:
- generated_from_trainer
model-index:
- name: assets
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: shc_deva_ds
      type: shc_deva_ds
      args: SHCAdverseEvents
    metrics:
    - type: f1
      value: 0.3333333333333333
      name: F1
---

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# assets

This model is a fine-tuned version of [iHealthGroup/shc-lm-v1](https://huggingface.co/iHealthGroup/shc-lm-v1) on the shc_deva_ds dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7051
- F1: 0.3333

## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.1628        | 0.62  | 400  | 0.7051          | 0.3333 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.13.0+cpu
- Datasets 2.4.0
- Tokenizers 0.11.6
