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# finetune_with_lora

This model is a fine-tuned version of [ruibin-wang/llama-7b-hf](https://huggingface.co/ruibin-wang/llama-7b-hf) on the customized 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 2
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results



### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.3

{"license": "other", "tags": ["generated_from_trainer"], "datasets": ["customized"], "model-index": [{"name": "finetune_with_lora", "results": []}]}
transformers pytorch llama text-generation generated_from_trainer dataset:customized license:other autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #llama #text-generation #generated_from_trainer #dataset-customized #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# finetune_with_lora

This model is a fine-tuned version of ruibin-wang/llama-7b-hf on the customized 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 2
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results



### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.3

# finetune_with_lora

This model is a fine-tuned version of ruibin-wang/llama-7b-hf on the customized 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 2
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0 ### Training results ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #llama #text-generation #generated_from_trainer #dataset-customized #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # finetune_with_lora

This model is a fine-tuned version of ruibin-wang/llama-7b-hf on the customized 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 2
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0 ### Training results ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #llama #text-generation #generated_from_trainer #dataset-customized #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# finetune_with_lora

This model is a fine-tuned version of ruibin-wang/llama-7b-hf on the customized 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 2
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0### Training results### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.3