pytorch tensorboard generated_from_trainer text-generation en dataset:keivalya/MedQuad-MedicalQnADataset license:apache-2.0 region:us
---
datasets:
- keivalya/MedQuad-MedicalQnADataset
language:
- en
license: apache-2.0
pipeline_tag: text-generation
tags:
- generated_from_trainer
model-index:
- name: MedAware
  results: []
---

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# MedAware

This model is a fine-tuned version of [euclaise/falcon_1b_stage2](https://huggingface.co/euclaise/falcon_1b_stage2) on MedQuAD: Medical Question Answering Dataset.

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1

### Training results

Training steps: 1025/1025; time- 2:45:21

| Steps | Training_loss |
|-------|---------------|
| 500   | 1.273800      |
| 1000  | 1.133000      |

TrainOutput(global_step=1025, training_loss=1.1994486794820647, metrics={'train_runtime': 9932.0844, 'train_samples_per_second': 1.652, 'train_steps_per_second': 0.103, 'total_flos': 3.2484758758785024e+16, 'train_loss': 1.1994486794820647, 'epoch': 1.0})

### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3