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RichardErkhov/
mlfoundations-dev_-_OH_original_wo_platypus-gguf

Name: mlfoundations-dev_-_OH_original_wo_platypus-gguf
Availability: InStock

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OH_original_wo_platypus - GGUF

Model creator: https://huggingface.co/mlfoundations-dev/
Original model: https://huggingface.co/mlfoundations-dev/OH_original_wo_platypus/

Name	Quant method	Size
OH_original_wo_platypus.Q2_K.gguf	Q2_K	2.96GB
OH_original_wo_platypus.IQ3_XS.gguf	IQ3_XS	3.28GB
OH_original_wo_platypus.IQ3_S.gguf	IQ3_S	3.43GB
OH_original_wo_platypus.Q3_K_S.gguf	Q3_K_S	3.41GB
OH_original_wo_platypus.IQ3_M.gguf	IQ3_M	3.52GB
OH_original_wo_platypus.Q3_K.gguf	Q3_K	3.74GB
OH_original_wo_platypus.Q3_K_M.gguf	Q3_K_M	3.74GB
OH_original_wo_platypus.Q3_K_L.gguf	Q3_K_L	4.03GB
OH_original_wo_platypus.IQ4_XS.gguf	IQ4_XS	4.18GB
OH_original_wo_platypus.Q4_0.gguf	Q4_0	4.34GB
OH_original_wo_platypus.IQ4_NL.gguf	IQ4_NL	4.38GB
OH_original_wo_platypus.Q4_K_S.gguf	Q4_K_S	4.37GB
OH_original_wo_platypus.Q4_K.gguf	Q4_K	4.58GB
OH_original_wo_platypus.Q4_K_M.gguf	Q4_K_M	4.58GB
OH_original_wo_platypus.Q4_1.gguf	Q4_1	4.78GB
OH_original_wo_platypus.Q5_0.gguf	Q5_0	5.21GB
OH_original_wo_platypus.Q5_K_S.gguf	Q5_K_S	5.21GB
OH_original_wo_platypus.Q5_K.gguf	Q5_K	5.34GB
OH_original_wo_platypus.Q5_K_M.gguf	Q5_K_M	5.34GB
OH_original_wo_platypus.Q5_1.gguf	Q5_1	5.65GB
OH_original_wo_platypus.Q6_K.gguf	Q6_K	6.14GB
OH_original_wo_platypus.Q8_0.gguf	Q8_0	7.95GB

Original model description:

library_name: transformers license: llama3.1 base_model: meta-llama/Llama-3.1-8B tags:

llama-factory
full
generated_from_trainer model-index:
name: OH_original_wo_platypus results: []

OH_original_wo_platypus

This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the mlfoundations-dev/OH_original_wo_platypus dataset. It achieves the following results on the evaluation set:

Loss: 0.6046

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: 5e-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 16
gradient_accumulation_steps: 4
total_train_batch_size: 512
total_eval_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 1738
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.6134	0.9985	328	0.6086
0.5568	2.0	657	0.5997
0.507	2.9954	984	0.6046

Framework versions

Transformers 4.45.2
Pytorch 2.3.0
Datasets 2.21.0
Tokenizers 0.20.1

RichardErkhov/mlfoundations-dev_-_OH_original_wo_platypus-gguf

Original model description:

OH_original_wo_platypus

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
mlfoundations-dev_-_OH_original_wo_platypus-gguf