cot-trainset-ft-transduction-v1-lora-train
This model is a fine-tuned version of barc0/cot-trainset-ft-transduction-v1 on the barc0/cot_transduction_train_dataset_960_ms10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1177
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.0918 | 1.0 | 155 | 0.0895 |
0.0463 | 2.0 | 310 | 0.0960 |
0.0271 | 3.0 | 465 | 0.1177 |
Framework versions
- PEFT 0.12.0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
- Downloads last month
- 10
Model tree for barc0/cot-trainset-ft-transduction-v1-lora-train
Base model
barc0/cot-trainset-ft-transduction-v1