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RichardErkhov/
tongliuphysics_-_zephyr0-7b-ultra-p-0.07-gguf

Name: tongliuphysics_-_zephyr0-7b-ultra-p-0.07-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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zephyr0-7b-ultra-p-0.07 - GGUF

Model creator: https://huggingface.co/tongliuphysics/
Original model: https://huggingface.co/tongliuphysics/zephyr0-7b-ultra-p-0.07/

Name	Quant method	Size
zephyr0-7b-ultra-p-0.07.Q2_K.gguf	Q2_K	2.53GB
zephyr0-7b-ultra-p-0.07.IQ3_XS.gguf	IQ3_XS	2.81GB
zephyr0-7b-ultra-p-0.07.IQ3_S.gguf	IQ3_S	2.96GB
zephyr0-7b-ultra-p-0.07.Q3_K_S.gguf	Q3_K_S	2.95GB
zephyr0-7b-ultra-p-0.07.IQ3_M.gguf	IQ3_M	3.06GB
zephyr0-7b-ultra-p-0.07.Q3_K.gguf	Q3_K	3.28GB
zephyr0-7b-ultra-p-0.07.Q3_K_M.gguf	Q3_K_M	3.28GB
zephyr0-7b-ultra-p-0.07.Q3_K_L.gguf	Q3_K_L	3.56GB
zephyr0-7b-ultra-p-0.07.IQ4_XS.gguf	IQ4_XS	3.67GB
zephyr0-7b-ultra-p-0.07.Q4_0.gguf	Q4_0	3.83GB
zephyr0-7b-ultra-p-0.07.IQ4_NL.gguf	IQ4_NL	3.87GB
zephyr0-7b-ultra-p-0.07.Q4_K_S.gguf	Q4_K_S	3.86GB
zephyr0-7b-ultra-p-0.07.Q4_K.gguf	Q4_K	4.07GB
zephyr0-7b-ultra-p-0.07.Q4_K_M.gguf	Q4_K_M	4.07GB
zephyr0-7b-ultra-p-0.07.Q4_1.gguf	Q4_1	4.24GB
zephyr0-7b-ultra-p-0.07.Q5_0.gguf	Q5_0	4.65GB
zephyr0-7b-ultra-p-0.07.Q5_K_S.gguf	Q5_K_S	4.65GB
zephyr0-7b-ultra-p-0.07.Q5_K.gguf	Q5_K	4.78GB
zephyr0-7b-ultra-p-0.07.Q5_K_M.gguf	Q5_K_M	4.78GB
zephyr0-7b-ultra-p-0.07.Q5_1.gguf	Q5_1	5.07GB
zephyr0-7b-ultra-p-0.07.Q6_K.gguf	Q6_K	5.53GB
zephyr0-7b-ultra-p-0.07.Q8_0.gguf	Q8_0	7.17GB

Original model description:

library_name: transformers license: mit base_model: HuggingFaceH4/mistral-7b-sft-beta tags:

trl
dpo
generated_from_trainer model-index:
name: zephyr0-7b-ultra-p-0.07 results: []

zephyr0-7b-ultra-p-0.07

This model is a fine-tuned version of HuggingFaceH4/mistral-7b-sft-beta on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4934
Rewards/chosen: -1.1822
Rewards/rejected: -2.0719
Rewards/accuracies: 0.75
Rewards/margins: 0.8897
Logps/rejected: -434.9780
Logps/chosen: -340.5889
Logits/rejected: -1.9202
Logits/chosen: -2.0197

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-07
train_batch_size: 2
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 128
total_eval_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.5521	0.2060	100	0.5258	-0.8611	-1.4030	0.6953	0.5419	-368.0812	-308.4762	-2.4729	-2.5388
0.5086	0.4119	200	0.5115	-1.1790	-1.8930	0.75	0.7140	-417.0868	-340.2655	-2.1594	-2.2382
0.49	0.6179	300	0.5050	-1.0454	-1.8769	0.7422	0.8316	-415.4766	-326.9024	-2.0191	-2.1080
0.4855	0.8239	400	0.4962	-1.1394	-2.0028	0.75	0.8634	-428.0682	-336.3091	-1.9714	-2.0677

Framework versions

Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.20.0

RichardErkhov/tongliuphysics_-_zephyr0-7b-ultra-p-0.07-gguf

Original model description:

zephyr0-7b-ultra-p-0.07

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
tongliuphysics_-_zephyr0-7b-ultra-p-0.07-gguf