Edit model card

chessgpt2-medium-s

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

  • Loss: 1.0790

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.025
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.3553 0.2560 1000 1.7539
1.6483 0.5119 2000 1.4751
1.4597 0.7679 3000 1.3417
1.3504 1.0238 4000 1.2587
1.2717 1.2798 5000 1.2104
1.2263 1.5357 6000 1.1654
1.1899 1.7917 7000 1.1346
1.154 2.0476 8000 1.1105
1.1124 2.3036 9000 1.0941
1.1002 2.5595 10000 1.0835
1.093 2.8155 11000 1.0790

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
Downloads last month
13
Safetensors
Model size
303M 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/chessgpt2-medium-s

Finetuned
(85)
this model