File size: 2,288 Bytes
fd4c228 9d08d4f fd4c228 9d08d4f fd4c228 9d08d4f fd4c228 9d08d4f fd4c228 |
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 |
---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-2
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-2_60-samples_config-1
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-2_60-samples_config-1
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-2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7095
## 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: 8
- total_train_batch_size: 8
- 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.0703 | 0.8696 | 5 | 1.0688 |
| 1.0003 | 1.9130 | 11 | 0.9209 |
| 0.9073 | 2.9565 | 17 | 0.8263 |
| 0.781 | 4.0 | 23 | 0.7580 |
| 0.7117 | 4.8696 | 28 | 0.7324 |
| 0.6407 | 5.9130 | 34 | 0.7095 |
| 0.5381 | 6.9565 | 40 | 0.7099 |
| 0.4646 | 8.0 | 46 | 0.7409 |
| 0.3692 | 8.8696 | 51 | 0.7878 |
| 0.2543 | 9.9130 | 57 | 0.8772 |
| 0.1333 | 10.9565 | 63 | 1.0029 |
| 0.0576 | 12.0 | 69 | 1.1541 |
| 0.03 | 12.8696 | 74 | 1.4092 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |