amy011872_-_LawToken-0.5B-a2-gguf – AI Model by RichardErkhov | AlphaNeural AI

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LawToken-0.5B-a2 - GGUF

Model creator: https://huggingface.co/amy011872/
Original model: https://huggingface.co/amy011872/LawToken-0.5B-a2/

Name	Quant method	Size
LawToken-0.5B-a2.Q2_K.gguf	Q2_K	0.33GB
LawToken-0.5B-a2.IQ3_XS.gguf	IQ3_XS	0.33GB
LawToken-0.5B-a2.IQ3_S.gguf	IQ3_S	0.33GB
LawToken-0.5B-a2.Q3_K_S.gguf	Q3_K_S	0.33GB
LawToken-0.5B-a2.IQ3_M.gguf	IQ3_M	0.33GB
LawToken-0.5B-a2.Q3_K.gguf	Q3_K	0.34GB
LawToken-0.5B-a2.Q3_K_M.gguf	Q3_K_M	0.34GB
LawToken-0.5B-a2.Q3_K_L.gguf	Q3_K_L	0.36GB
LawToken-0.5B-a2.IQ4_XS.gguf	IQ4_XS	0.34GB
LawToken-0.5B-a2.Q4_0.gguf	Q4_0	0.34GB
LawToken-0.5B-a2.IQ4_NL.gguf	IQ4_NL	0.34GB
LawToken-0.5B-a2.Q4_K_S.gguf	Q4_K_S	0.37GB
LawToken-0.5B-a2.Q4_K.gguf	Q4_K	0.38GB
LawToken-0.5B-a2.Q4_K_M.gguf	Q4_K_M	0.38GB
LawToken-0.5B-a2.Q4_1.gguf	Q4_1	0.36GB
LawToken-0.5B-a2.Q5_0.gguf	Q5_0	0.38GB
LawToken-0.5B-a2.Q5_K_S.gguf	Q5_K_S	0.4GB
LawToken-0.5B-a2.Q5_K.gguf	Q5_K	0.4GB
LawToken-0.5B-a2.Q5_K_M.gguf	Q5_K_M	0.4GB
LawToken-0.5B-a2.Q5_1.gguf	Q5_1	0.4GB
LawToken-0.5B-a2.Q6_K.gguf	Q6_K	0.48GB
LawToken-0.5B-a2.Q8_0.gguf	Q8_0	0.51GB

Original model description:

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

trl
sft
generated_from_trainer datasets:
generator model-index:
name: LawToken-0.5B-a2 results: []

LawToken-0.5B-a2

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

Loss: 0.8634

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.03
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss
1.14	0.14	10000	1.1605
1.0485	0.28	20000	1.0663
1.0592	0.42	30000	1.0069
0.9293	0.56	40000	0.9609
0.8503	0.71	50000	0.9210
0.9322	0.85	60000	0.8858
0.8238	0.99	70000	0.8634

Framework versions

Transformers 4.38.2
Pytorch 2.3.0a0+ebedce2
Datasets 2.19.1
Tokenizers 0.15.2