OLMo-1B-SFT-hf
This model is a fine-tuned version of allenai/OLMo-1B-hf on the allenai/tulu-v2-sft-mixture dataset. It achieves the following results on the evaluation set:
- Loss: 0.8224
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: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.1754 | 0.9992 | 1236 | 1.0556 |
| 0.9628 | 1.9993 | 2473 | 0.8751 |
| 0.801 | 2.9977 | 3708 | 0.8224 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.19.1
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