hoganpham_-_my_first_clm_model-gguf – AI Model by RichardErkhov | AlphaNeural AI

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hoganpham_-_my_first_clm_model-gguf

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my_first_clm_model - GGUF

Model creator: https://huggingface.co/hoganpham/
Original model: https://huggingface.co/hoganpham/my_first_clm_model/

Name	Quant method	Size
my_first_clm_model.Q2_K.gguf	Q2_K	0.06GB
my_first_clm_model.IQ3_XS.gguf	IQ3_XS	0.07GB
my_first_clm_model.IQ3_S.gguf	IQ3_S	0.07GB
my_first_clm_model.Q3_K_S.gguf	Q3_K_S	0.07GB
my_first_clm_model.IQ3_M.gguf	IQ3_M	0.07GB
my_first_clm_model.Q3_K.gguf	Q3_K	0.07GB
my_first_clm_model.Q3_K_M.gguf	Q3_K_M	0.07GB
my_first_clm_model.Q3_K_L.gguf	Q3_K_L	0.07GB
my_first_clm_model.IQ4_XS.gguf	IQ4_XS	0.07GB
my_first_clm_model.Q4_0.gguf	Q4_0	0.08GB
my_first_clm_model.IQ4_NL.gguf	IQ4_NL	0.08GB
my_first_clm_model.Q4_K_S.gguf	Q4_K_S	0.08GB
my_first_clm_model.Q4_K.gguf	Q4_K	0.08GB
my_first_clm_model.Q4_K_M.gguf	Q4_K_M	0.08GB
my_first_clm_model.Q4_1.gguf	Q4_1	0.08GB
my_first_clm_model.Q5_0.gguf	Q5_0	0.09GB
my_first_clm_model.Q5_K_S.gguf	Q5_K_S	0.09GB
my_first_clm_model.Q5_K.gguf	Q5_K	0.09GB
my_first_clm_model.Q5_K_M.gguf	Q5_K_M	0.09GB
my_first_clm_model.Q5_1.gguf	Q5_1	0.09GB
my_first_clm_model.Q6_K.gguf	Q6_K	0.1GB
my_first_clm_model.Q8_0.gguf	Q8_0	0.12GB

Original model description:

library_name: transformers license: apache-2.0 base_model: distilbert/distilgpt2 tags:

generated_from_trainer datasets:
eli5_category model-index:
name: my_first_clm_model results: []

my_first_clm_model

This model is a fine-tuned version of distilbert/distilgpt2 on the eli5_category dataset. It achieves the following results on the evaluation set:

Loss: 3.8306

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss
3.973	1.0	660	3.8421
3.8975	2.0	1320	3.8328
3.8628	3.0	1980	3.8306

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.2.0
Tokenizers 0.19.1