Tanysha_-_STC-large-gguf – AI Model by RichardErkhov | AlphaNeural AI

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STC-large - GGUF

Model creator: https://huggingface.co/Tanysha/
Original model: https://huggingface.co/Tanysha/STC-large/

Name	Quant method	Size
STC-large.Q2_K.gguf	Q2_K	0.08GB
STC-large.Q3_K_S.gguf	Q3_K_S	0.08GB
STC-large.Q3_K.gguf	Q3_K	0.09GB
STC-large.Q3_K_M.gguf	Q3_K_M	0.09GB
STC-large.Q3_K_L.gguf	Q3_K_L	0.1GB
STC-large.IQ4_XS.gguf	IQ4_XS	0.1GB
STC-large.Q4_0.gguf	Q4_0	0.1GB
STC-large.IQ4_NL.gguf	IQ4_NL	0.1GB
STC-large.Q4_K_S.gguf	Q4_K_S	0.1GB
STC-large.Q4_K.gguf	Q4_K	0.11GB
STC-large.Q4_K_M.gguf	Q4_K_M	0.11GB
STC-large.Q4_1.gguf	Q4_1	0.11GB
STC-large.Q5_0.gguf	Q5_0	0.11GB
STC-large.Q5_K_S.gguf	Q5_K_S	0.11GB
STC-large.Q5_K.gguf	Q5_K	0.12GB
STC-large.Q5_K_M.gguf	Q5_K_M	0.12GB
STC-large.Q5_1.gguf	Q5_1	0.12GB
STC-large.Q6_K.gguf	Q6_K	0.13GB
STC-large.Q8_0.gguf	Q8_0	0.17GB

Original model description:

library_name: transformers license: mit base_model: gpt2 tags:

generated_from_trainer model-index:
name: STC-large results: []

STC-large

This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0792

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
lr_scheduler_warmup_steps: 1000
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss
1.4996	2.0	500	0.1021
0.113	4.0	1000	0.0829
0.0757	6.0	1500	0.0798
0.0625	8.0	2000	0.0778
0.0572	10.0	2500	0.0783
0.0547	12.0	3000	0.0787
0.0531	14.0	3500	0.0792

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0