File size: 2,401 Bytes
6bf30ac 51aed32 6bf30ac 51aed32 6bf30ac 51aed32 6bf30ac 51aed32 6bf30ac |
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 |
---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-1_auto
- GaetanMichelet/chat-120_ft_task-1_auto
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-1_120-samples_config-2_auto
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-31-8B_task-1_120-samples_config-2_auto
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) on the GaetanMichelet/chat-60_ft_task-1_auto and the GaetanMichelet/chat-120_ft_task-1_auto datasets.
It achieves the following results on the evaluation set:
- Loss: 0.8840
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.1727 | 0.9091 | 5 | 1.2190 |
| 1.1492 | 2.0 | 11 | 1.0507 |
| 0.9803 | 2.9091 | 16 | 1.0035 |
| 0.8687 | 4.0 | 22 | 0.9365 |
| 0.7872 | 4.9091 | 27 | 0.9064 |
| 0.7171 | 6.0 | 33 | 0.8840 |
| 0.5563 | 6.9091 | 38 | 0.9091 |
| 0.4878 | 8.0 | 44 | 1.0011 |
| 0.3849 | 8.9091 | 49 | 1.0698 |
| 0.2449 | 10.0 | 55 | 1.1907 |
| 0.1483 | 10.9091 | 60 | 1.3620 |
| 0.1039 | 12.0 | 66 | 1.4585 |
| 0.0637 | 12.9091 | 71 | 1.6115 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |