pythia-2.8b-sft
This model is a fine-tuned version of EleutherAI/pythia-2.8b on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.6671
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.8621 | 0.0442 | 100 | 1.7438 |
1.7909 | 0.0884 | 200 | 1.7135 |
1.7775 | 0.1327 | 300 | 1.7020 |
1.7587 | 0.1769 | 400 | 1.6937 |
1.7683 | 0.2211 | 500 | 1.6876 |
1.7488 | 0.2653 | 600 | 1.6824 |
1.7646 | 0.3096 | 700 | 1.6799 |
1.7557 | 0.3538 | 800 | 1.6776 |
1.7485 | 0.3980 | 900 | 1.6743 |
1.7368 | 0.4422 | 1000 | 1.6729 |
1.7298 | 0.4865 | 1100 | 1.6705 |
1.7525 | 0.5307 | 1200 | 1.6724 |
1.7386 | 0.5749 | 1300 | 1.6703 |
1.7325 | 0.6191 | 1400 | 1.6684 |
1.7306 | 0.6633 | 1500 | 1.6682 |
1.7262 | 0.7076 | 1600 | 1.6669 |
1.7333 | 0.7518 | 1700 | 1.6675 |
1.7318 | 0.7960 | 1800 | 1.6673 |
1.7293 | 0.8402 | 1900 | 1.6668 |
1.7326 | 0.8845 | 2000 | 1.6671 |
1.7378 | 0.9287 | 2100 | 1.6668 |
1.7259 | 0.9729 | 2200 | 1.6671 |
Framework versions
- PEFT 0.17.0
- Transformers 4.55.0
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
- Downloads last month
- 108
Model tree for quyanh/pythia-2.8b-sft
Base model
EleutherAI/pythia-2.8b