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RichardErkhov/
EEG123_-_subject2-test1-gguf

Name: EEG123_-_subject2-test1-gguf
Availability: InStock

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gguf

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Quantization made by Richard Erkhov.

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subject2-test1 - GGUF

Model creator: https://huggingface.co/EEG123/
Original model: https://huggingface.co/EEG123/subject2-test1/

Name	Quant method	Size
subject2-test1.Q2_K.gguf	Q2_K	1.27GB
subject2-test1.IQ3_XS.gguf	IQ3_XS	1.38GB
subject2-test1.IQ3_S.gguf	IQ3_S	1.44GB
subject2-test1.Q3_K_S.gguf	Q3_K_S	1.44GB
subject2-test1.IQ3_M.gguf	IQ3_M	1.49GB
subject2-test1.Q3_K.gguf	Q3_K	1.57GB
subject2-test1.Q3_K_M.gguf	Q3_K_M	1.57GB
subject2-test1.Q3_K_L.gguf	Q3_K_L	1.69GB
subject2-test1.IQ4_XS.gguf	IQ4_XS	1.71GB
subject2-test1.Q4_0.gguf	Q4_0	1.79GB
subject2-test1.IQ4_NL.gguf	IQ4_NL	1.79GB
subject2-test1.Q4_K_S.gguf	Q4_K_S	1.8GB
subject2-test1.Q4_K.gguf	Q4_K	1.88GB
subject2-test1.Q4_K_M.gguf	Q4_K_M	1.88GB
subject2-test1.Q4_1.gguf	Q4_1	1.95GB
subject2-test1.Q5_0.gguf	Q5_0	2.11GB
subject2-test1.Q5_K_S.gguf	Q5_K_S	2.11GB
subject2-test1.Q5_K.gguf	Q5_K	2.16GB
subject2-test1.Q5_K_M.gguf	Q5_K_M	2.16GB
subject2-test1.Q5_1.gguf	Q5_1	2.28GB
subject2-test1.Q6_K.gguf	Q6_K	2.46GB
subject2-test1.Q8_0.gguf	Q8_0	3.19GB

Original model description:

library_name: transformers license: llama3.2 base_model: meta-llama/Llama-3.2-3B tags:

alignment-handbook
trl
sft
generated_from_trainer
trl
sft
generated_from_trainer datasets:
EEG123/DE_subject_2 model-index:
name: subject2-test1 results: []

subject2-test1

This model is a fine-tuned version of meta-llama/Llama-3.2-3B on the EEG123/DE_subject_2 dataset. It achieves the following results on the evaluation set:

Loss: 1.0319

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: 1e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.3241	1.0	377	0.5891
0.0017	2.0	754	1.2835
0.0009	3.0	1131	1.0319

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

RichardErkhov/EEG123_-_subject2-test1-gguf

Original model description:

subject2-test1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
EEG123_-_subject2-test1-gguf