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library_name: transformers
license: apache-2.0
base_model: allenai/OLMo-7B-hf
tags:
- generated_from_trainer
model-index:
- name: OLmo-chebl_domain_adaption
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-chebl_domain_adaption
This model is a fine-tuned version of [allenai/OLMo-7B-hf](https://huggingface.co/allenai/OLMo-7B-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3516
- Model Preparation Time: 0.0043
## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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: 0.05
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|:-------------:|:------:|:----:|:---------------:|:----------------------:|
| 6.3473 | 0.0710 | 50 | 6.2448 | 0.0043 |
| 4.8393 | 0.1419 | 100 | 4.6801 | 0.0043 |
| 3.2501 | 0.2129 | 150 | 3.2598 | 0.0043 |
| 2.7432 | 0.2839 | 200 | 2.8011 | 0.0043 |
| 2.4688 | 0.3549 | 250 | 2.4233 | 0.0043 |
| 2.2724 | 0.4258 | 300 | 2.2580 | 0.0043 |
| 2.1390 | 0.4968 | 350 | 2.1196 | 0.0043 |
| 1.9718 | 0.5678 | 400 | 2.0202 | 0.0043 |
| 1.8871 | 0.6388 | 450 | 1.9191 | 0.0043 |
| 1.8967 | 0.7097 | 500 | 1.8318 | 0.0043 |
| 1.7147 | 0.7807 | 550 | 1.7578 | 0.0043 |
| 1.7526 | 0.8517 | 600 | 1.7118 | 0.0043 |
| 1.6391 | 0.9226 | 650 | 1.6556 | 0.0043 |
| 1.5693 | 0.9936 | 700 | 1.6024 | 0.0043 |
| 1.4872 | 1.0639 | 750 | 1.5712 | 0.0043 |
| 1.4543 | 1.1348 | 800 | 1.5263 | 0.0043 |
| 1.4862 | 1.2058 | 850 | 1.4896 | 0.0043 |
| 1.3994 | 1.2768 | 900 | 1.4550 | 0.0043 |
| 1.2903 | 1.3478 | 950 | 1.4253 | 0.0043 |
| 1.2909 | 1.4187 | 1000 | 1.4001 | 0.0043 |
| 1.2847 | 1.4897 | 1050 | 1.3812 | 0.0043 |
| 1.2536 | 1.5607 | 1100 | 1.3681 | 0.0043 |
| 1.2414 | 1.6317 | 1150 | 1.3592 | 0.0043 |
| 1.3003 | 1.7026 | 1200 | 1.3541 | 0.0043 |
| 1.3042 | 1.7736 | 1250 | 1.3523 | 0.0043 |
| 1.3176 | 1.8446 | 1300 | 1.3517 | 0.0043 |
| 1.2306 | 1.9155 | 1350 | 1.3516 | 0.0043 |
| 1.2716 | 1.9865 | 1400 | 1.3515 | 0.0043 |
| 1.3064 | 2.0 | 1410 | 1.3516 | 0.0043 |
### Framework versions
- Transformers 5.9.0
- Pytorch 2.8.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2
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