Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
mistral-finetuned-samsum – AI Model by fbellame | AlphaNeural AI
You can deploy this model and start earning money today!
fbellame
/
mistral-finetuned-samsum
like
0
peft
tensorboard
safetensors
generated_from_trainer
TheBloke/Mistral-7B-Instruct-v0.1-GPTQ
adapter
apache-2.0
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
mistral-finetuned-samsum
This model is a fine-tuned version of
TheBloke/Mistral-7B-Instruct-v0.1-GPTQ
on the None dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
The following
bitsandbytes
quantization config was used during training:
quant_method: gptq
bits: 4
tokenizer: None
dataset: None
group_size: 128
damp_percent: 0.1
desc_act: True
sym: True
true_sequential: True
use_cuda_fp16: False
model_seqlen: None
block_name_to_quantize: None
module_name_preceding_first_block: None
batch_size: 1
pad_token_id: None
use_exllama: False
max_input_length: None
exllama_config: {'version': <ExllamaVersion.ONE: 1>}
cache_block_outputs: True
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 0.0002
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
training_steps: 50
mixed_precision_training: Native AMP
Training results
Framework versions
PEFT 0.7.0
Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
