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SmolLM-1.7B-sft-160k
rasyosef/SmolLM-1.7B-sft-160k
SmolLM-1.7B-sft-160k is a machine learning model from rasyosef. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Aug 10, 2024
- Updated
- Aug 11, 2024
- SHA
- 7105acfe
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
SmolLM-1.7B-sft-160k
This model is a fine-tuned version of HuggingFaceTB/SmolLM-1.7B on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 1.1601
- Model Preparation Time: 0.0348
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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|---|---|---|---|---|
| 1.1547 | 0.0518 | 200 | 1.1745 | 0.0348 |
| 1.1416 | 0.1037 | 400 | 1.1734 | 0.0348 |
| 1.1334 | 0.1555 | 600 | 1.1720 | 0.0348 |
| 1.1415 | 0.2073 | 800 | 1.1710 | 0.0348 |
| 1.1399 | 0.2591 | 1000 | 1.1697 | 0.0348 |
| 1.1448 | 0.3110 | 1200 | 1.1685 | 0.0348 |
| 1.1429 | 0.3628 | 1400 | 1.1673 | 0.0348 |
| 1.1368 | 0.4146 | 1600 | 1.1665 | 0.0348 |
| 1.1309 | 0.4664 | 1800 | 1.1656 | 0.0348 |
| 1.1429 | 0.5183 | 2000 | 1.1646 | 0.0348 |
| 1.1474 | 0.5701 | 2200 | 1.1638 | 0.0348 |
| 1.1311 | 0.6219 | 2400 | 1.1633 | 0.0348 |
| 1.126 | 0.6737 | 2600 | 1.1625 | 0.0348 |
| 1.1356 | 0.7256 | 2800 | 1.1618 | 0.0348 |
| 1.1329 | 0.7774 | 3000 | 1.1613 | 0.0348 |
| 1.129 | 0.8292 | 3200 | 1.1610 | 0.0348 |
| 1.1347 | 0.8811 | 3400 | 1.1605 | 0.0348 |
| 1.1305 | 0.9329 | 3600 | 1.1602 | 0.0348 |
| 1.1278 | 0.9847 | 3800 | 1.1601 | 0.0348 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Aug 10, 2024
- Updated
- Aug 11, 2024