chessgpt-medium-m – AI Model by dakwi | AlphaNeural AI

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dakwi/
chessgpt-medium-m

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text-generation

generated_from_trainer

openai-community/gpt2-medium

autotrain_compatible

text-generation-inference

endpoints_compatible

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chessgpt-medium-m

This model is a fine-tuned version of gpt2-medium on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.9777

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: 0.0003
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.2
num_epochs: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.6517	0.08	250	1.5222
1.4486	0.16	500	1.3596
1.3463	0.24	750	1.2706
1.2623	0.32	1000	1.1986
1.2115	0.4	1250	1.1483
1.167	0.48	1500	1.1158
1.1327	0.56	1750	1.0757
1.1058	0.64	2000	1.0555
1.0798	0.72	2250	1.0320
1.0585	0.8	2500	1.0099
1.0435	0.88	2750	0.9929
1.0276	0.96	3000	0.9811

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1