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# hh-lmgym-demo-lora

This model is a fine-tuned version of [EleutherAI/gpt-j-6b](https://huggingface.co/EleutherAI/gpt-j-6b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6836
- Accuracy: 0.0896
- Entropy: 1.6709

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 99
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Entropy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|
| 1.6617        | 1.0   | 3466 | 1.6855          | 0.0896   | 1.6784  |
| 1.66          | 2.0   | 6932 | 1.6836          | 0.0896   | 1.6709  |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0-rc1
- Datasets 2.7.1
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "model-index": [{"name": "hh-lmgym-demo-lora", "results": []}]}
pytorch generated_from_trainer license:apache-2.0 region:us
TAGS
#pytorch #generated_from_trainer #license-apache-2.0 #region-us 

hh-lmgym-demo-lora
==================


This model is a fine-tuned version of EleutherAI/gpt-j-6b on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.6836
* Accuracy: 0.0896
* Entropy: 1.6709


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: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 99
* distributed\_type: multi-GPU
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* num\_epochs: 2.0


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0-rc1
* Datasets 2.7.1
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 99
* distributed\_type: multi-GPU
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* num\_epochs: 2.0 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0-rc1
* Datasets 2.7.1
* Tokenizers 0.13.3
TAGS
#pytorch #generated_from_trainer #license-apache-2.0 #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 1e-05
* train\_batch\_size: 2
* eval\_batch\_size: 8
* seed: 99
* distributed\_type: multi-GPU
* gradient\_accumulation\_steps: 16
* total\_train\_batch\_size: 32
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: cosine
* lr\_scheduler\_warmup\_ratio: 0.03
* num\_epochs: 2.0 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 2.0.0-rc1
* Datasets 2.7.1
* Tokenizers 0.13.3