cot-trainset-ft-transduction-v4-lora-train
This model is a fine-tuned version of barc0/cot-transduction-arc-heavy on the barc0/cot_train_dataset_960_ms10_v2, the barc0/cot_rearc_dataset_100_ms10 and the barc0/seeds_cot datasets. It achieves the following results on the evaluation set:
- Loss: 0.1497
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.103 | 0.9983 | 287 | 0.1445 |
| 0.0874 | 1.9965 | 574 | 0.1497 |
Framework versions
- PEFT 0.12.0
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
barc0/cot-transduction-arc-heavy