84 lines
2.3 KiB
Markdown
84 lines
2.3 KiB
Markdown
---
|
|
library_name: transformers
|
|
license: apache-2.0
|
|
base_model: HuggingFaceTB/SmolLM2-135M
|
|
tags:
|
|
- smol-course
|
|
- module_1
|
|
- trl
|
|
- sft
|
|
- trl
|
|
- sft
|
|
- generated_from_trainer
|
|
model-index:
|
|
- name: SmolLM2-FT-MyDataset
|
|
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. -->
|
|
|
|
# SmolLM2-FT-MyDataset
|
|
|
|
This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M](https://huggingface.co/HuggingFaceTB/SmolLM2-135M) on an unknown dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.9266
|
|
|
|
## 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: 5e-05
|
|
- train_batch_size: 4
|
|
- eval_batch_size: 8
|
|
- seed: 42
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
|
- lr_scheduler_type: linear
|
|
- training_steps: 1000
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss |
|
|
|:-------------:|:------:|:----:|:---------------:|
|
|
| 1.0161 | 0.0982 | 50 | 1.0429 |
|
|
| 0.9943 | 0.1965 | 100 | 1.0086 |
|
|
| 0.953 | 0.2947 | 150 | 0.9906 |
|
|
| 0.9561 | 0.3929 | 200 | 0.9802 |
|
|
| 0.9585 | 0.4912 | 250 | 0.9699 |
|
|
| 0.9394 | 0.5894 | 300 | 0.9597 |
|
|
| 0.9284 | 0.6876 | 350 | 0.9535 |
|
|
| 0.9237 | 0.7859 | 400 | 0.9462 |
|
|
| 0.8945 | 0.8841 | 450 | 0.9402 |
|
|
| 0.9043 | 0.9823 | 500 | 0.9348 |
|
|
| 0.7479 | 1.0806 | 550 | 0.9421 |
|
|
| 0.805 | 1.1788 | 600 | 0.9388 |
|
|
| 0.7359 | 1.2770 | 650 | 0.9382 |
|
|
| 0.7437 | 1.3752 | 700 | 0.9365 |
|
|
| 0.7778 | 1.4735 | 750 | 0.9336 |
|
|
| 0.7678 | 1.5717 | 800 | 0.9317 |
|
|
| 0.7452 | 1.6699 | 850 | 0.9301 |
|
|
| 0.7373 | 1.7682 | 900 | 0.9279 |
|
|
| 0.738 | 1.8664 | 950 | 0.9269 |
|
|
| 0.7513 | 1.9646 | 1000 | 0.9266 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.44.2
|
|
- Pytorch 2.10.0+cu128
|
|
- Datasets 4.0.0
|
|
- Tokenizers 0.19.1
|