File size: 2,625 Bytes
a1ef4fc |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
---
license: apache-2.0
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: HuggingFaceTB/SmolLM-1.7B-Instruct
datasets:
- generator
model-index:
- name: SmolLM_1_7B_Instruct_qlora_nf4_merged
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. -->
# SmolLM_1_7B_Instruct_qlora_nf4_merged
This model is a fine-tuned version of [HuggingFaceTB/SmolLM-1.7B-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-1.7B-Instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6129
## 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: 0.001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 2.088 | 0.9524 | 10 | 1.9222 |
| 1.8671 | 2.0 | 21 | 1.7931 |
| 1.7735 | 2.9524 | 31 | 1.7340 |
| 1.7236 | 4.0 | 42 | 1.6932 |
| 1.6739 | 4.9524 | 52 | 1.6680 |
| 1.652 | 6.0 | 63 | 1.6494 |
| 1.6354 | 6.9524 | 73 | 1.6379 |
| 1.6139 | 8.0 | 84 | 1.6288 |
| 1.5938 | 8.9524 | 94 | 1.6233 |
| 1.5828 | 10.0 | 105 | 1.6189 |
| 1.5722 | 10.9524 | 115 | 1.6164 |
| 1.5588 | 12.0 | 126 | 1.6149 |
| 1.5539 | 12.9524 | 136 | 1.6141 |
| 1.5506 | 14.0 | 147 | 1.6134 |
| 1.5437 | 14.9524 | 157 | 1.6132 |
| 1.5427 | 16.0 | 168 | 1.6130 |
| 1.5407 | 16.9524 | 178 | 1.6130 |
| 1.5386 | 18.0 | 189 | 1.6130 |
| 1.5373 | 18.9524 | 199 | 1.6130 |
| 1.5397 | 19.0476 | 200 | 1.6129 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.0
- Datasets 2.18.0
- Tokenizers 0.19.1 |