ccore-v3

This model is a fine-tuned version of ccore/ccore-v3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5452

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: 0.0001
  • train_batch_size: 24
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 192
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 15 0.5351
No log 2.0 30 0.5292
No log 3.0 45 0.5297
No log 4.0 60 0.5342
No log 5.0 75 0.5368
No log 6.0 90 0.5420
No log 7.0 105 0.5422
No log 8.0 120 0.5438
No log 9.0 135 0.5452
No log 9.3540 140 0.5452

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0
Downloads last month
128
Safetensors
Model size
125M params
Tensor type
F32
·
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.

Model tree for ccore/ccore-v3

Unable to build the model tree, the base model loops to the model itself. Learn more.