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# medicare-gpt2-large

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the pubmed-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6383

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 5.9036        | 0.08  | 500  | 4.2296          |
| 3.7554        | 0.16  | 1000 | 3.3542          |
| 3.2457        | 0.23  | 1500 | 3.0897          |
| 3.065         | 0.31  | 2000 | 2.9694          |
| 2.966         | 0.39  | 2500 | 2.8919          |
| 2.8912        | 0.47  | 3000 | 2.8305          |
| 2.8345        | 0.55  | 3500 | 2.7817          |
| 2.7818        | 0.62  | 4000 | 2.7378          |
| 2.7391        | 0.7   | 4500 | 2.7001          |
| 2.7052        | 0.78  | 5000 | 2.6689          |
| 2.6769        | 0.86  | 5500 | 2.6486          |
| 2.6599        | 0.94  | 6000 | 2.6383          |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

### Test input samples
diabetes is caused by
{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["pubmed-summarization"], "model-index": [{"name": "medicare-gpt2-large", "results": []}]}
transformers pytorch tensorboard gpt2 text-generation generated_from_trainer dataset:pubmed-summarization license:mit autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #dataset-pubmed-summarization #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

medicare-gpt2-large
===================


This model is a fine-tuned version of gpt2 on the pubmed-summarization dataset.
It achieves the following results on the evaluation set:


* Loss: 2.6383


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: 0.0005
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 1
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3


### Test input samples


diabetes is caused by



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 1
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3 ### Test input samples


diabetes is caused by
TAGS
#transformers #pytorch #tensorboard #gpt2 #text-generation #generated_from_trainer #dataset-pubmed-summarization #license-mit #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0005
* train\_batch\_size: 32
* eval\_batch\_size: 32
* seed: 42
* gradient\_accumulation\_steps: 8
* total\_train\_batch\_size: 256
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_steps: 1000
* num\_epochs: 1
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3 ### Test input samples


diabetes is caused by