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RichardErkhov/
mlfoundations-dev_-_oh_v1.3_metamath_x4-gguf

Name: mlfoundations-dev_-_oh_v1.3_metamath_x4-gguf
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oh_v1.3_metamath_x4 - GGUF

Model creator: https://huggingface.co/mlfoundations-dev/
Original model: https://huggingface.co/mlfoundations-dev/oh_v1.3_metamath_x4/

Name	Quant method	Size
oh_v1.3_metamath_x4.Q2_K.gguf	Q2_K	2.96GB
oh_v1.3_metamath_x4.IQ3_XS.gguf	IQ3_XS	3.28GB
oh_v1.3_metamath_x4.IQ3_S.gguf	IQ3_S	3.43GB
oh_v1.3_metamath_x4.Q3_K_S.gguf	Q3_K_S	3.41GB
oh_v1.3_metamath_x4.IQ3_M.gguf	IQ3_M	3.52GB
oh_v1.3_metamath_x4.Q3_K.gguf	Q3_K	3.74GB
oh_v1.3_metamath_x4.Q3_K_M.gguf	Q3_K_M	3.74GB
oh_v1.3_metamath_x4.Q3_K_L.gguf	Q3_K_L	4.03GB
oh_v1.3_metamath_x4.IQ4_XS.gguf	IQ4_XS	4.18GB
oh_v1.3_metamath_x4.Q4_0.gguf	Q4_0	4.34GB
oh_v1.3_metamath_x4.IQ4_NL.gguf	IQ4_NL	4.38GB
oh_v1.3_metamath_x4.Q4_K_S.gguf	Q4_K_S	4.37GB
oh_v1.3_metamath_x4.Q4_K.gguf	Q4_K	4.58GB
oh_v1.3_metamath_x4.Q4_K_M.gguf	Q4_K_M	4.58GB
oh_v1.3_metamath_x4.Q4_1.gguf	Q4_1	4.78GB
oh_v1.3_metamath_x4.Q5_0.gguf	Q5_0	5.21GB
oh_v1.3_metamath_x4.Q5_K_S.gguf	Q5_K_S	5.21GB
oh_v1.3_metamath_x4.Q5_K.gguf	Q5_K	5.34GB
oh_v1.3_metamath_x4.Q5_K_M.gguf	Q5_K_M	5.34GB
oh_v1.3_metamath_x4.Q5_1.gguf	Q5_1	5.65GB
oh_v1.3_metamath_x4.Q6_K.gguf	Q6_K	6.14GB
oh_v1.3_metamath_x4.Q8_0.gguf	Q8_0	7.95GB

Original model description:

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

llama-factory
full
generated_from_trainer model-index:
name: oh_v1.3_metamath_x4 results: []

oh_v1.3_metamath_x4

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on the mlfoundations-dev/oh_v1.3_metamath_x4 dataset. It achieves the following results on the evaluation set:

Loss: 0.6809

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: 8
gradient_accumulation_steps: 8
total_train_batch_size: 512
total_eval_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
0.6908	0.9992	310	0.6929
0.6425	1.9984	620	0.6802
0.605	2.9976	930	0.6809

Framework versions

Transformers 4.46.1
Pytorch 2.3.0
Datasets 3.1.0
Tokenizers 0.20.3

RichardErkhov/mlfoundations-dev_-_oh_v1.3_metamath_x4-gguf

Original model description:

oh_v1.3_metamath_x4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
mlfoundations-dev_-_oh_v1.3_metamath_x4-gguf