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RichardErkhov/
yangzhao02_-_qwen2-0.5b-sft-gguf

Name: yangzhao02_-_qwen2-0.5b-sft-gguf
Availability: InStock

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qwen2-0.5b-sft - GGUF

Model creator: https://huggingface.co/yangzhao02/
Original model: https://huggingface.co/yangzhao02/qwen2-0.5b-sft/

Name	Quant method	Size
qwen2-0.5b-sft.Q2_K.gguf	Q2_K	0.32GB
qwen2-0.5b-sft.Q3_K_S.gguf	Q3_K_S	0.31GB
qwen2-0.5b-sft.Q3_K.gguf	Q3_K	0.33GB
qwen2-0.5b-sft.Q3_K_M.gguf	Q3_K_M	0.33GB
qwen2-0.5b-sft.Q3_K_L.gguf	Q3_K_L	0.34GB
qwen2-0.5b-sft.IQ4_XS.gguf	IQ4_XS	0.33GB
qwen2-0.5b-sft.Q4_0.gguf	Q4_0	0.33GB
qwen2-0.5b-sft.IQ4_NL.gguf	IQ4_NL	0.33GB
qwen2-0.5b-sft.Q4_K_S.gguf	Q4_K_S	0.36GB
qwen2-0.5b-sft.Q4_K.gguf	Q4_K	0.37GB
qwen2-0.5b-sft.Q4_K_M.gguf	Q4_K_M	0.37GB
qwen2-0.5b-sft.Q4_1.gguf	Q4_1	0.35GB
qwen2-0.5b-sft.Q5_0.gguf	Q5_0	0.37GB
qwen2-0.5b-sft.Q5_K_S.gguf	Q5_K_S	0.38GB
qwen2-0.5b-sft.Q5_K.gguf	Q5_K	0.39GB
qwen2-0.5b-sft.Q5_K_M.gguf	Q5_K_M	0.39GB
qwen2-0.5b-sft.Q5_1.gguf	Q5_1	0.39GB
qwen2-0.5b-sft.Q6_K.gguf	Q6_K	0.47GB
qwen2-0.5b-sft.Q8_0.gguf	Q8_0	0.49GB

Original model description:

license: apache-2.0 base_model: Qwen/Qwen2-0.5B tags:

alignment-handbook
trl
sft
generated_from_trainer
trl
sft
generated_from_trainer datasets:
HuggingFaceH4/ultrachat_200k model-index:
name: qwen2-0.5b-sft results: []

Visualize in Weights & Biases

qwen2-0.5b-sft

This model is a fine-tuned version of Qwen/Qwen2-0.5B on the HuggingFaceH4/ultrachat_200k dataset. It achieves the following results on the evaluation set:

Loss: 1.5269

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 8
total_train_batch_size: 128
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.524	0.9999	1888	1.5269

Framework versions

Transformers 4.42.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

RichardErkhov/yangzhao02_-_qwen2-0.5b-sft-gguf

Original model description:

qwen2-0.5b-sft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
yangzhao02_-_qwen2-0.5b-sft-gguf