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---
license: apache-2.0
base_model: allenai/OLMo-1B-hf
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- allenai/tulu-v2-sft-mixture
model-index:
- name: OLMo-1B-SFT-hf
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# OLMo-1B-SFT-hf
This model is a fine-tuned version of [allenai/OLMo-1B-hf](https://huggingface.co/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
|