
> 🚧 Note: this repo is only for demo purpose, current uploaded version is finetuned version of KoRWKV which is ~20% trained ckpt (with ~31Billion tokens) 🚧

# beomi/KoAlpaca-KoRWKV-1.5B (v1.0)

This model is a fine-tuned version of [KoRWKV-1.5B](https://huggingface.co/beomi/KoRWKV-1.5B) on a KoAlpaca Dataset v1.0

Dataset available at [KoAlpaca Github Repository](https://github.com/Beomi/KoAlpaca)

## Training procedure

### Train Device

- A100 80G x2
- ~2hrs

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 2.0
- mixed_precision_training: Native AMP fp16

### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

{"language": ["ko"], "license": "apache-2.0", "tags": ["KoRWKV", "KoAlpaca"], "datasets": ["KoAlpaca-v1.0"], "pipeline_tag": "text-generation", "base_model": "KoRWKV-1.5B", "model-index": [{"name": "KoAlpaca-KoRWKV-1.5B", "results": []}]}
transformers pytorch rwkv text-generation KoRWKV KoAlpaca ko dataset:KoAlpaca-v1.0 base_model:KoRWKV-1.5B license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #rwkv #text-generation #KoRWKV #KoAlpaca #ko #dataset-KoAlpaca-v1.0 #base_model-KoRWKV-1.5B #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 


>  Note: this repo is only for demo purpose, current uploaded version is finetuned version of KoRWKV which is ~20% trained ckpt (with ~31Billion tokens) 

# beomi/KoAlpaca-KoRWKV-1.5B (v1.0)

This model is a fine-tuned version of KoRWKV-1.5B on a KoAlpaca Dataset v1.0

Dataset available at KoAlpaca Github Repository

## Training procedure

### Train Device

- A100 80G x2
- ~2hrs

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 2.0
- mixed_precision_training: Native AMP fp16

### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2

# beomi/KoAlpaca-KoRWKV-1.5B (v1.0)

This model is a fine-tuned version of KoRWKV-1.5B on a KoAlpaca Dataset v1.0

Dataset available at KoAlpaca Github Repository ## Training procedure ### Train Device

- A100 80G x2
- ~2hrs ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 2.0
- mixed_precision_training: Native AMP fp16 ### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #rwkv #text-generation #KoRWKV #KoAlpaca #ko #dataset-KoAlpaca-v1.0 #base_model-KoRWKV-1.5B #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # beomi/KoAlpaca-KoRWKV-1.5B (v1.0)

This model is a fine-tuned version of KoRWKV-1.5B on a KoAlpaca Dataset v1.0

Dataset available at KoAlpaca Github Repository ## Training procedure ### Train Device

- A100 80G x2
- ~2hrs ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 2.0
- mixed_precision_training: Native AMP fp16 ### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2