Edit model card

chessgpt-medium-l

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

  • Loss: 0.7634

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
1.4326 0.064 1000 1.3596
1.2424 0.128 2000 1.1829
1.1278 0.192 3000 1.0753
1.0296 0.256 4000 0.9877
0.9605 0.32 5000 0.9224
0.9193 0.384 6000 0.8874
0.8911 0.448 7000 0.8600
0.8707 0.512 8000 0.8405
0.8521 0.576 9000 0.8221
0.8391 0.64 10000 0.8089
0.8242 0.704 11000 0.7972
0.8146 0.768 12000 0.7858
0.8047 0.832 13000 0.7769
0.7974 0.896 14000 0.7701
0.7916 0.96 15000 0.7651

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1
Downloads last month
398
Safetensors
Model size
355M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for dakwi/chessgpt-medium-l

Finetuned
(94)
this model