File size: 2,618 Bytes
0f35b76 09ea778 ba96ecf 09ea778 0f35b76 ba96ecf 0f35b76 ba96ecf 0f35b76 ba96ecf 0f35b76 ba96ecf 0f35b76 |
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 89 |
---
library_name: transformers
license: llama3.2
base_model: tanliboy/llama-3.2-3b
tags:
- trl
- sft
- alignment-handbook
- generated_from_trainer
model-index:
- name: llama-3.2-3b-sft
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. -->
# llama-3.2-3b-sft
This model is a fine-tuned version of [tanliboy/llama-3.2-3b](https://huggingface.co/tanliboy/llama-3.2-3b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7216
## 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: 3e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8741 | 0.0448 | 100 | 0.8600 |
| 0.8038 | 0.0897 | 200 | 0.8095 |
| 0.7937 | 0.1345 | 300 | 0.7789 |
| 0.7712 | 0.1794 | 400 | 0.7644 |
| 0.7393 | 0.2242 | 500 | 0.7565 |
| 0.7458 | 0.2691 | 600 | 0.7506 |
| 0.7694 | 0.3139 | 700 | 0.7458 |
| 0.713 | 0.3587 | 800 | 0.7422 |
| 0.7347 | 0.4036 | 900 | 0.7387 |
| 0.7243 | 0.4484 | 1000 | 0.7356 |
| 0.7161 | 0.4933 | 1100 | 0.7331 |
| 0.7247 | 0.5381 | 1200 | 0.7308 |
| 0.7477 | 0.5830 | 1300 | 0.7288 |
| 0.7429 | 0.6278 | 1400 | 0.7273 |
| 0.7317 | 0.6726 | 1500 | 0.7256 |
| 0.7226 | 0.7175 | 1600 | 0.7243 |
| 0.695 | 0.7623 | 1700 | 0.7234 |
| 0.7167 | 0.8072 | 1800 | 0.7226 |
| 0.686 | 0.8520 | 1900 | 0.7221 |
| 0.7214 | 0.8969 | 2000 | 0.7218 |
| 0.7358 | 0.9417 | 2100 | 0.7216 |
| 0.7259 | 0.9865 | 2200 | 0.7216 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|